每日最新頭條.有趣資訊

Gartner 2018 數據庫魔力象限:阿里雲上榜

作者:Merv Adrian、Donald Feinberg 和 Nick Heudecker

在競爭日益激烈的市場,評估OPDBMS方案的數據和分析主管必須兼顧當前需求和未來需求。非關係型和基於雲數據庫的供應商為全球企業提供了新的機會,企業可以利用這份魔力象限在更新改造方面做出更明智的選擇。

戰略性規劃假設

到2019年,為雲DBMS架構設計的存儲資源和計算資源實現分離將成為主導性的數據庫平台即服務(dbPaaS)模式,也會開始出現在本地環境(on-premises)。

到2020年,基於開源的DBMS產品將佔DBMS收入的20%以上,這將加大其對主流買家的吸引力。

到2020年,關係數據庫技術將繼續用於至少70%的新應用和新項目。

到2023年,所有數據庫中75%將放在雲平台上,這個動向將顯著改變DBMS供應商的格局。

市場定義/描述

操作型數據庫管理系統(OPDBMS)市場的主角是適合用來支持業務流程的傳統事務的關係和非關係數據庫管理產品。其中包括一系列廣泛的企業級應用軟體,既指外購的業務應用軟體,比如ERP和CRM應用軟體,也指定製的事務系統。我們對這個市場的定義還包括支持面向物聯網的互動和事件處理(傳輸中數據)的DBMS產品。

按照Gartner的定義,OPDMBS管理的工作負載包括如下:

批量加載

實時或持續的數據加載

並發的在線和基於Web的新穎/更新事務

操作型報告

管理外部分布式流程,比如“備份”(look-aside)查詢

OPDBMS產品必須提供對這些工作負載劃定優先級的功能,以便它們在並發運行時,滿足服務級別協定(SLA)。

Gartner對DBMS的定義是用於定義、創建、更新、管理和查詢數據庫的一套完整軟體系統。這裡的術語“數據庫”是指有組織的數據集,這些數據可能有多種格式,存儲在某種形式的存儲介質中(存儲介質包括傳統硬碟、閃存、固態硬碟和DRAM)。數據庫必須包括這種機制:隔離和管理工作負載需求,並在數據的託管實例裡面控制最終用戶訪問的各個參數。此外,DBMS應提供與獨立程式和工具聯繫的接口,並允許和管理多種類型的並發工作負載的高效運行。不存在這個前提:DBMS非得支持關係模式或如今使用的可能全部類型的數據。此外,我們的定義並未規定DBMS必須是閉源產品,還包括商業支持的開源DBMS產品。

OPDBMS可以支持多種不同的交付模式,比如獨立的DBMS軟體、雲(公共雲和私有雲)映像或容器化版本、符合認證的配置以及數據庫設備。分析每一家供應商時,一起討論和評估這些模式。

在這份魔力象限中,我們將供應商的所有OPDBMS產品視為一套。如果某供應商銷售可用作OPDBMS的多款DBMS產品,我們會在介紹這家供應商的部分中加以描述,但我們將該供應商的所有產品作為一個整體加以評估。如果任何“優勢”和“注意事項”涉及一款或多款特定的產品,會在介紹供應商的部分中予以注明。由於選擇範圍越來越廣,買家更常注重單項最佳策略,企業組織評估不同供應商的產品很重要。

Gartner 2018 年操作型數據庫管理系統魔力象限:

Gartner 2017 年操作型數據庫管理系統魔力象限:

Gartner 2016 年操作型數據庫管理系統魔力象限:

Gartner 2015 年操作型數據庫管理系統魔力象限:

新增和跌出的廠商

由於市場不斷變化,我們相應審查並調整了魔力象限的入圍標準。由於這番調整,入圍任何魔力象限的供應商組合可能會隨時間而變化。一家供應商出現在某一年的魔力象限,但未出現在下一年的魔力象限,這未必表明我們改變了對這家供應商的看法。這可能表明了市場發生變化、因而評估標準發生變化,或者這家供應商關注的重心發生變化。

新增

Actian

阿里雲

MongoDB

跌出:一家都沒有

雲頭條摘選了比較受關注的三家供應商的優勢和注意事項翻譯發布,供各位讀者參考,其他公司內容請參考英文版:

阿里雲

阿里雲是一家全球雲計算公司,總部在中國杭州,國際總部在新加坡。它提供眾多的服務,比如:支持MySQL(基於阿里雲AliSQL)/SQL Server/PostgreSQL的ApsaraDB for RDS(關係數據庫服務)、ApsaraDB for Redis、POLARDB、HybridDB for MySQL及PostgreSQL,以及Elastic MapReduce for Hadoop。此外,Apsara Stack提供本地私有雲實施。

優勢

廣泛的產品組合:阿里雲擁有的DBMS服務品種是這份魔力象限中雲服務提供商(CSP)中最廣的。雖然它缺少寬列非關係模式(比如用於Apache Cassandra),但除此之外的模式都可供選擇;而且在許多情況下,有多種選擇(比如PostgreSQL版和MySQL版)。阿里雲擁有為數不多的針對時間序列的雲端產品之一,即HiTSDB。它還有面向EnterpriseDB Postgres Plus和MariaDB的託管服務。

市場佔有率:據Gartner的DBMS市場數據顯示,阿里雲在2017年攀升至第12位,較2016年增長88%,當時還排在第20位。阿里雲是中國最大的雲提供商,但也支持中國境外的10個數據中心區域,2個在美國。與亞馬遜相似,阿里雲以零售行業起家,這讓它有望作為全球四大或五大CSP中的一員,繼續增長。

雲和混合模式的潛力:阿里雲推銷的Apsara Stack是一款面向本地部署的完整私有雲。這與AWS和谷歌雲平台相比具有競爭優勢。它還讓阿里雲有可能跨所有服務,在雲環境和本地環境之間共享數據――其他大多數CSP做不到這點。此外,它為所有的Apsara DBMS產品提供了“平移”( lift and shift)靈活性。

注意事項

重心在中國:阿里雲是中國的一家CSP,雖然國際總部在新加坡。這種安排存在兩個問題。首先,想與美國的各大CSP競爭,阿里雲就需要大幅增加其在美國境外的區域數據中心的數量(出於政治原因,它無法依賴美國境內的大幅增長勢頭)。其次,阿里雲的DBMS產品組合中大部分只在中國境內可用。這讓產品無法被世界上的其他地區使用――幾個調查對象強調了這個限制因素。

功能、成本和支持:雖然阿里雲的大多數調查得分都是平均值,但自動數據分發和高速事務處理的得分卻遠低於平均值。這些功能對於物聯網和高端生產系統來說很重要。此外,幾個調查對象提到高成本和不一致的支持是兩大問題。此外,鑒於阿里雲實現的高增長率,支持是老大難問題。

Serverless模式和產品集成:阿里雲的大多數DBMS服務是獨立的,最近才憑借POLARDB增添了Serverless模式。雖然阿里雲幾乎擁有客戶所需的每一種DBMS模式,但選擇正確的模式並將其集成到應用軟體中卻很困難。此外,Serverless模式現在必不可少,以便在集成來自多個服務的數據時降低成本並增強靈活性。

AWS

AWS是亞馬遜的全資子公司,總部位於美國華盛頓州西雅圖。AWS提供Amazon DynamoDB(非關係文檔和鍵值DBMS)、Amazon ElastiCache(提供Redis和Memcached)、Amazon Neptune(圖形DBMS),以及Amazon Elastic MapReduce(EMR)Hadoop發行版。它還銷售亞馬遜關係數據庫服務(Amazon RDS),其關係數據庫引擎支持MariaDB、Microsoft SQL Server、MySQL和Oracle,以及支持MySQL和PostgreSQL的Amazon Aurora。

優勢

市場發展勢頭:2017年,作為基礎設施即服務(IaaS)和平台即服務(PaaS)兩大產品市場的絕對CSP長官者,AWS的DBMS收入增長了一倍以上(連續第二年),超過SAP,奪得第四位。產品組合繼續擴大,增加了RDS產品,比如Aurora for PostgreSQL和Aurora for MySQL、面向圖形使用場景的Amazon Neptune,以及在開發和數據移動方面日益扮演重要角色的AWS Glue。AWS為其數據庫遷移服務制定了積極大膽的路線圖,並實現了既定目標,這加快了遷移到雲、願意考慮替代DBMS的客戶採用新產品的步伐。亞馬遜聲稱,截至2018年5月,70000個客戶遷移了數據庫。

快速交付:AWS經常添加新的功能、區域和相關產品,以挑戰傳統產品的長官地位。比如說,DynamoDB新增了“生存時間”特性、用DynamoDB加速器(DAX)進行加速、自動擴展、靜態加密、按需備份和時間點恢復等功能。AWS的調查分數反映了它對於大多數工作負載而言有多強的競爭力。雖然它並非在任何類別都居於領先,但只在專業服務、雲/混合部署和可調優的一致性方面低於平均值。AWS積極尋求國際認證,在此過程中打破了前幾年阻礙客戶採用雲的眾多障礙。

加快合作和垂直市場活動:AWS合作夥伴網絡在2017年新增了10000個成員,聲稱其60%的合作夥伴在美國境外。AWS Marketplace現在提供4200多個軟體列表。AWS新增了在支持基於vSphere的私有雲的Amazon RDS方面與VMware集成的功能,這為混合部署使用場景提供了契機。AWS已派出了涉及16個職能領域的行銷團隊、銷售團隊和谘詢團隊,覆蓋垂直市場、遷移和AP支持等使用場景,以及存儲和DevOps等技術專業領域。

注意事項

有限的本地功能:AWS僅在雲端提供其服務。雖然一些AWS產品基於本地產品,也有強大的遷移服務,但缺少本地版本對一些企業組織來說卻是限制因素。接受調查的客戶給AWS所打的分接近雲/混合部署的最低值。AWS最近宣布與VMware建立合作夥伴關係,還宣布了與相應的本地DBMS聯繫的連接件,以便在混合環境中起到幫助。

來自零售競爭對手的阻力:雖然AWS有許多零售客戶,但仍然有一種看法:與亞馬遜競爭的組織(比如電子商務和零售公司)不應該使用AWS,因為這麽做只會便宜了競爭對手(即AWS)。一些為谷歌雲平台提供參考客戶的大型零售商已公開承認:在證明了谷歌雲的價值,並確信谷歌的能力之後,從AWS遷移到了谷歌。

糟糕的專業服務結果:在參考客戶調查中,AWS的專業服務得分最低,不止一個標準偏差(STD)低於平均值。一些客戶認為不同的設計假設是個挑戰,自己不知道該如何應對;另一些客戶提到了AWS的遷移工具相對不成熟。AWS最近努力加強與領先服務提供商的合作夥伴關係,有望改善情形。

谷歌

Google總部位於美國加利福尼亞州芒廷維尤,是Alphabet控股公司的全資子公司。谷歌雲平台(GCP)旗下的谷歌dbPaaS產品包括:Cloud Spanner關係DBMS(RDBMS)、Cloud Bigtable、支持非關係DBMS使用場景的Cloud Datastore、支持記憶體數據存儲的Cloud Memorystore for Redis、Firebase實時數據庫,以及支持移動應用的Cloud Firestore(測試版)。為了支持其他平台中的數據,谷歌提供了支持託管版MySQL和PostgreSQL的Cloud SQL。谷歌還與許多數據庫供應商建立了合作夥伴關係,以便在虛擬機上輕鬆創建和管理數據庫映像。

優勢

託管服務交付:接受調查的參考客戶盛讚GCP的OPDBMS管理功能,因此該公司在操作易用性方面得分最高,在總體滿意度方面得分第二。但是,一些參考客戶表示希望更深入地了解DBMS操作和調優。這表明公司企業要轉變文化,才能充分利用GCP的託管服務。

不斷擴大的合作夥伴生態系統:去年,谷歌與思科、NetApp、Salesforce和SAP等大型企業軟體供應商建立了合作夥伴關係。谷歌還在深耕針對SaaS合作夥伴的計劃,並承諾所有的銷售、專業服務和行銷活動都有100%的合作夥伴參與率。

客戶可享用的技術管道:四分之三的谷歌參考客戶稱自己願意採用比較新、風險比較高的技術。這對谷歌來說是件好事,因為它經常在產品生命周期的早期階段為客戶提供新穎的和更新後的產品,以便獲得即時反饋。參考客戶很欣賞這種可享用性,因為這讓它們能夠更早地規劃採用,並保持領先競爭對手。

注意事項

功能不足:谷歌的參考客戶中有三分之一表示,GCP OPDBMS套件功能差或缺少功能。參考客戶具體提到了與以下幾方面有關的不足:更豐富的客戶端庫、更精細的身份及訪問管理功能、查詢分析、操作工具以及預算管理方面的可見性。此外,谷歌在數據庫活動監控方面從參考客戶處獲得的分數是倒數第二。

支持方面的挑戰:參考客戶提到了一級支持方面的問題,在這方面給谷歌所打的分接近所有供應商中的最低值。它們提到了對請求和操作問題的響應速度低於預期,除非問題上報到專門的產品團隊,否則不太可能得到解決。

滯後的市場意識:該魔力象限調查的450多個參考客戶中有15%評估了GCP,但最終沒有選擇。與去年的6%相比,這個數字已有了大幅提高,但評估率仍然落後於GCP最直接的競爭對手,而且差距明顯。雖然谷歌在提高GCP能力的知名度方面還有大量工作要做,但谘詢Gartner的用戶卻對GCP產品表示了越來越濃厚的興趣。

Actian

Actian, which is headquartered in Palo Alto, California, U.S., offers Actian X Hybrid Database for combined operational and analytical processing, NoSQL Object Database and Zen Embedded Database by subscription-based and perpetual licensing. Actian X began shipping in April 2017 as a free upgrade to Ingres, which is nearly four decades old. Half of the Ingres customer base is European. A managed service is available, but no database platform as a service (dbPaaS).

Strengths

Loyal customers: Most of the Actianreference customers we surveyed had been using Ingres for over 10 years. Its low maintenance requirement was singled out as a key reason for this. Ingres is the standard DBMS in half of Actian’s reference customers.

Renewed product investment: Actian X Hybrid Database combines Ingres with the X100 engine of Actian’s Vector offering to create a real-time updatable column store with features such as single instruction, multiple data (SIMD) vector processing, chip cache exploitation, and automatic storage indexes for reducing I/O. In addition, Actian partners with Esri, Safe Software and others to enhance its spatial tools.

Suitability of Zen for edge and IoT uses: Actian Zen Embedded Database is a purpose-built self-tuning, zero database administrator (DBA) offering with multiple licensing models. In addition to Windows and Linux, it supports Android, Raspbian, Windows 10 IoT Core and Nano Server. Instances can share data without extraction, transformation and loading (ETL), and DataConnect data integration ties Zen devices and Zen gateways to Vector and Actian X to create end-to-end data flows.

Cautions

Lateness of key enterprise features and multimodel support: Online patching is not possible, nor are Java stored procedures. There is no continuous statistics collection or continuous tuning, and Actian has not yet begun to create internal machine learning (ML)-based optimization. Synchronization of the in-memory column store requires the creation of triggers and stored procedures. As yet, there is no document support via JavaScript Object Notation (JSON) or XML, graph or linked data types. This will make it difficult for Actian to capture the new workloads that are behind much new business.

Customer dissatisfaction: Actian received several survey sentiment scores greater than one standard deviation (STD) below the mean, including for value, negotiation, overall product capabilities, integration and deployment, and service and support. Respondents singled out cloud/hybrid deployment, high availability/disaster recovery (HA/DR), automated data distribution, and gaps in security, such as the absence of data masking and poor database activity monitoring.

Poor customer upgrade momentum: Actian’s customer loyalty is a double-edged sword, as three-quarters of its customers are running a version three or more releases behind the latest. The company still offers no dbPaaS version that could help with upgrade paths and new trials.

DataStax

DataStax, which is based in Santa Clara, California, U.S., provides DataStax Enterprise (DSE), a nonrelational multimodel DBMS in an integrated platform. DSE is aimed at mixed workloads and built on the Apache Cassandra DBMS, with wide-column, key-value and document/JSON support, plus a graph store. The product is available in two subscription package levels: Basic and Max. There are two add-on options: DSE Analytics Solo and DSE Graph. DSE is available on-premises, through multiple cloud providers and for hybrid cloud deployment. DataStax also offers a managed dbPaaS, DataStax Managed Cloud, in multiple public cloud environments.

Strengths

Cloud offerings and data distribution: DataStax Managed Cloud, introduced in 2017, has proven a solid offering, resulting in a survey score for cloud/hybrid deployment greater than one STD above the mean. The score for automated data distribution was also up (from 2017) to one STD above the mean, aided by the availability of additional management capabilities for shards and nodes.

Service, support and professional services: Many survey respondents identified customer support as a strength, stating that they were happy they chose to pay for support. This demonstrates that DataStax has increased the quality of these services over the past year. Survey scores for these areas rose from one STD below the mean in 2017 to the average score for all vendors in 2018.

Go-to-market and sales strategy: DataStax has revamped its go-to-market strategy to target specific prospects, and this, coupled with vertical-segment sales support, resulted in a 50% increase in growth from 2016 to 2017. DataStax must continue to pursue this strategy and change the market’s perception that it is leaving behind open-source Cassandra.

Cautions

Negotiations and pricing: Reference customers for DataStax identified difficulties with negotiating contracts and gave it a survey score for negotiations well below the mean. These difficulties are also mentioned by Gartner clients during interactions with analysts. This is a consistent theme with open-source vendors as they attempt to balance open-source pricing with creation of revenue opportunities.

Ease of operations and programming: Survey scores for both these aspects of DataStax’s offering were well below the mean, and many respondents mentioned the need for professional services and education to use the product effectively. Respondents claimed that more upfront education and planning were required, although they described the education that was provided as excellent.

Open-source perception: Gartner’s inquiry service continues to receive questions about DataStax’s apparent withdrawal from the Apache Software Foundation. Although we believe DataStax remains committed to the Apache Cassandra project, DataStax must continue to assure existing and prospective customers of its continued commitment. DataStax remains the primary contributor of bug fixes and new functionality.

EnterpriseDB

EnterpriseDBis aprivately held vendor based in Boston, Massachusetts, U.S. It sells the EDB Postgres Platform, based on the PostgreSQL open-source DBMS. It offers Developer, Standard and Enterprise subscriptions. There is also a private cloud built on OpenStack, and the Postgres Plus Cloud Database (PPCD) dbPaaS service. EDB Postgres Ark is a framework for provisioning databases in multiple cloud platforms. EDB Postgres is an operational DBMS standard at over half the company’s surveyed reference customers, where it has typically been in production for four years or more.

Strengths

Growth and community leverage: EnterpriseDB’s revenue grew by over 30% in 2017. It participates in the sizable Postgres community; releases typically follow closely upon the open-source version. Its website offers free introductory training on demand.

Improving functional richness and hybrid deployment:EDB Postgres Ark integrates with AWS, Azure and OpenStack to provide more hands-on operational control. EDB Replication Server supports deployments spanning clouds and on-premises environments, with Data Adapters for Oracle, Microsoft SQL Server and SAP ASE. The addition of TimescaleDB, the Postgres array type and AgensGraph (Cypher-based) enhances EnterpriseDB’s relatively full SQL capabilities, which include arrays and windowing, declarative table partitioning, publish-subscribe and quorum commits.

Steady customer satisfaction: Surveyed reference customers highlighted EnterpriseDB’s value. Its improvement in last year’s survey in terms of overall customer satisfaction was continued in this year’s survey, with solid middle-of-the-pack scores. A new customer success program is in place to build on these advances.

Cautions

Performance scores and feature expectations: Surveyed reference customers scored EDB Postgres more than one STD below the mean for automated data distribution capabilities, high-speed data ingestion and high-speed transaction processing. Comments highlighted the absence of zero-downtime upgrades, autotuning and an in-memory column store. Security also scored below average. Although EnterpriseDB offers a pioneering Postgres Security Evaluation Service, customers noted the absence of data masking and activity monitoring. In addition, they deemed the auditing capability limited.

Competitive environment: Cloud platform vendors now all offer some type of PostgreSQL dbPaaS. Their opportunity to optimize for their own managed storage represents a significant threat to EnterpriseDB. On-premises, additional Postgres-based vendors are gaining some visibility. For Oracle replacement opportunities, MariaDB now competes with its implementation of Oracle’s Procedural Language/Structured Query Language (PL/SQL) in its MySQL-based offering.

Ecosystem building: Adoption by third-party software vendors remains a challenge for EnterpriseDB (except for its existing relationship with Infor), especially in the application space. EnterpriseDB relies on resellers in southern Europe, Japan and Latin America for sales and Tier 1 and 2 support. The company claims to have products in development with major system integrators and expanded partnerships with Alibaba, Hewlett Packard Enterprise, IBM and Red Hat, and its work with Quest and Pivotal is now in market. This is, therefore, an area in which EnterpriseDB is improving.

IBM

IBM, which is based in Armonk, New York, U.S., offers Db2 for Linux, UNIX and Windows (LUW), Db2 for z/OS, Db2 Hosted, Db2 on Cloud, Db2 Event Store, the Db2 Analytics Accelerator appliance, IBM Graph, Information Management System (IMS) and Informix. There is also IBM Compose for several open-source managed DBMSs (including non-IBM ones) in the cloud, and IBM Cloudant (proprietary but based on Apache CouchDB).

Strengths

Rich features and open-source support: Db2 LUW and Db2 for z/OS have rich feature sets. IBM also has fully compatible managed cloud (Db2 on Cloud) and Db2 Hosted cloud offerings, in addition to its Db2 on-premises offerings. Although many of IBM’s surveyed reference customers mentioned that IBM is slow to deliver new features, they also praised its strong feature set. Further, many praised IBM’s support for, and delivery of, open-source components integrated into its commercial products.

Availability and stability: IBM Db2 is well known for its high availability and stability as a DBMS, especially in the case of Db2 for z/OS. IBM also offers Db2 pureScale, which adds capabilities similar to those of Db2 LUW. The majority of IBM’s reference customers mentioned these features and gave IBM high scores for HA/DR.

Service and support: IBM has traditionally offered great service and support through a global organization that includes a partner program with global reach. This has not changed. This year, 90% of IBM’s surveyed reference customers made at least one positive comment about the quality and timeliness of service and support from IBM’s customer support and field support teams.

Cautions

Sales execution: IBM continues to struggle with its sales and marketing model, as evidenced by a continued decline in its DBMS revenue, which fell again in 2017, according to Gartner’s information. Several reference customers remarked that IBM’s sales model has identified too many sales silos and that it is difficult to navigate. Our conversations with Gartner clients indicate that Db2 is seldom shortlisted, even when the client already has it. IBM’s new digital marketing effort will help by simplifying the sales model for data management products. IBM must fix its sales and marketing model if it is to reverse the downward trend.

Cloud and hybrid deployment: For the second year, IBM received an overall score one STD below the mean for cloud and hybrid deployment in the reference customer survey. Although IBM has a wealth of cloud DBMS products, it appears that customers struggle to integrate on-premises and cloud systems.

Pricing: IBM has long struggled with complex pricing models, and this year, its surveyed reference customers identified this as a major problem. For both suitability of pricing method and satisfaction with value for price, IBM scored the lowest of all the vendors in the survey, at greater than one STD below the mean. In addition, respondents identified IBM’s pricing as the thing they most disliked about its products. However, we believe IBM’s new digital marketing effort and the pricing and packaging changes made more than a year ago (although slow to be adopted by customers) will improve its pricing.

InterSystems

InterSystems, which is based in Cambridge, Massachusetts, U.S., was founded in 1978. Building on the success of Caché, a hybrid, multimodel DBMS supporting relational and nonrelational access, InterSystems introduced the IRIS Data Platform in January 2018 to increase its focus on scalability heterogeneous data and fast data. InterSystems maintains its position in the top eight DBMS vendors, in Gartner’s estimation, although it is lagging slightly behind the overall market’s growth as it focuses on adding the new offering to its portfolio.

Strengths

Functionality: InterSystems’ multimodel DBMSs support SQL across object and nonrelational models. In addition, a Spark connector and Predictive Model Markup Language (PMML) support expanded heterogeneous data enablement. Surveyed reference customers identified flexibility and functionality as key advantages, and gave good scores for security features. Multitenant capabilities and the InterSystems Cloud Manager, a tool that provides, deploys and manages the IRIS Data Platform on the cloud of choice, offer a path to hybrid and cloud deployment for partners — a key part of the company’s strategy.

Loyal customer base: Reference customers continue to indicate they will increase their usage for InterSystems’ products. InterSystems’ high score for perceived value is helped by its support being included in the licensing model, although the licensing model itself received some negative comments. InterSystems is introducing new cloud-based licensing models and no-cost development licenses. Furthermore, it is expanding beyond its strong healthcare base by gaining customers in the finance and manufacturing sectors.

Stability and support: In general, InterSystems again received excellent scores from reference customers for minimal downtime and for overall service and support. However, its geographic expansion has exposed a need to improve its service and support in Asia/Pacific.

Cautions

Market awareness: InterSystems is correctly perceived as being primarily active in the healthcare sector, which still represents 80% of its customer base. Continued strong marketing in other industry segments, such as finance and manufacturing, based on growing success, is imperative. In addition, InterSystems is still heavily focused on North America. It also lacks its own dbPaaS, which may prevent it uncovering more opportunities.

Skills and functionality: A recurring theme in previous Magic Quadrant assessments of InterSystems has been that relevant skills are hard to find — even though reference customers describe implementation as easy. Additionally, there remain gaps in terms of mobile features and heterogeneous replication. InterSystems has not yet begun to use internal ML for operational management, or to ease its essentially “do it yourself” approach to geospatial and time series use cases.

Documentation: InterSystems has typically scored below the average for its documentation. This year there were fewer complaints, but documentation remains a concern, especially for a product that still requires different skills that are in short supply.

MapR

MapR, which is based in Santa Clara, California, U.S., provides the MapR Data Platform, which includes MapR-DB, MapR-XD for file and container support, and MapR Streams. Optional Hadoop, Spark and ML components are also available. MapR-DB is a multimodel OPDBMS compatible with the Apache HBase API. MapR also offers a small-footprint version of its Data Platform, called MapR Edge, that is suitable for IoT-style deployments. The Data Platform is available on-premises and through various cloud providers.

Strengths

Support and professional services: Reference customers gave MapR the second-highest overall score for its support and professional services organization. They were particularly impressed by the advantages of its Quick Start program, which is used to accelerate deployment and delivery of business outcomes

Overall satisfaction: MapR tied for the highest overall score from reference customers for organizational satisfaction. It received the second-highest score from reference customers for its HA/DR facilities.

Diverse platform vision: MapR continues to close functional gaps and build features comparable to those of much larger companies. Its operational and analytical convergence, coupled with a platform spanning on-premises, cloud and edge deployments, makes it unique among competitors of similar size.

Cautions

Usability challenges: Surveyed reference customers gave MapR’s product the second-lowest overall score for ease of programming. They also identified usability challenges, with administrative tooling, for example, being considered merely adequate and therefore in need of user interface and user experience improvements. MapR has introduced a developer portal to help developers become productive more quickly.

Open-source compatibility and support: Reference customers routinely criticize MapR for its lagging support for the most current versions of popular open-source projects, and for its lack of support for projects used in the broader Hadoop ecosystem. In addition, development around Apache Drill, promoted as MapR’s primary analytical engine, appears to have slowed during the past year.

Market visibility and direction: MapR has always struggled to attain the same level of market visibility as its competitors. It continues to move toward a comprehensive developer-targeted proposition centered on containers and analytics, which could prove challenging to sell in a market that is increasingly buying fit-for-purpose platforms, particularly in the cloud.

MarkLogic

MarkLogic, which is based in San Carlos, California, U.S., offers a nonrelational multimodel DBMS, which it describes as “operational and transactional.” The product is available in two editions: Essential Enterprise and a free developer edition. Essential Enterprise can be deployed in on-premises environments and in clouds (both as an image and as a PaaS, the MarkLogic Query Service), including those offered by AWS, Microsoft (Azure) and Google (GCP). MarkLogic also supports containers, natively.

Strengths

Execution: MarkLogic has focused on execution over the past year, with great results — it maintains its position as the top Challenger. With its focus on global growth, it now derives 30% of its revenue from outside North America. Its expansion into new industries (with vertical solutions) and a growing partner ecosystem have yielded strong results. MarkLogic’s implementation of a subscription license model (although not open-source), has been well received, with a survey score one STD above the mean for value for money.

Functionality and security: Reference customers scored MarkLogic one STD above the mean for multimodel, cloud and hybrid deployment and security. Security has become a focus of the DBMS market, and MarkLogic scored above the mean in all security areas, its highest score being for activity monitoring. Many survey respondents praised the flexibility of MarkLogic’s multimodel capabilities (especially for graphing). They also praised its search capabilities, an original feature of the product.

Service and support: MarkLogic’s reference customer scores for service and support were above the mean. Additionally, respondents praised the quality of its support and the level of involvement of its service organization. These comments help to explain the product’s reliability, which is demonstrated by the lowest outage number of any vendor in this Magic Quadrant.

Cautions

Developer skills and training: MarkLogic scored far above the mean for documentation and training, which was far better than in the previous survey, but many respondents again identified difficulty finding developer skills. Many also expressed surprise at the level of training necessary to use the product effectively. In addition, they expressed a desire to have spent more time in the planning phases of projects, as they believe this would have reduced the difficulties they encountered using the product.

Adoption challenges: MarkLogic’s survey scores for integration with other DBMS environments and deployment were far below the mean. Many respondents commented on difficulties in these areas, stating that they required professional services from MarkLogic or partners to solve problems, and that they needed assistance with implementation. We believe this is caused more by MarkLogic’s DBMS being nonrelational than by a deficiency in the MarkLogic DBMS.

Competitive landscape: Competition to MarkLogic is growing in two areas. First, its vision of a data platform focused on unifying data silos, which was innovative but early, is now being pursued by many vendors, including incumbent vendors and Hadoop distributors offering data platforms. Second, almost all vendors are moving to multimodel DBMSs and supporting a document-style model with JSON support. MarkLogic must continue to focus on its data platform and define its next innovative step.

Microsoft

Microsoft, based in Redmond, Washington, U.S., markets its SQL Server DBMS and Azure SQL Database (a DBMS PaaS based on SQL Server) as flagship products for the OPDBMS market. It also markets Azure Cosmos DB, a nonrelational, globally distributed document DBMS PaaS solution that is compatible with SQL, Azure Tables, MongoDB, Cassandra and Gremlin graph APIs.

Strengths

Market-leading execution: Gartner’s 2017 data for the DBMS market shows that Microsoft’s revenue has grown above the market rate for the past four years, with the cloud accounting for an increasingly large part of its revenue. After introducing multiple cloud-based services in the past few years, Microsoft is now focused on building a cohesive experience across its portfolio.

Breadth of portfolio and capabilities: Microsoft has created a far-reaching portfolio with both its on-premises and cloud-based offerings. Its portfolio, once strongly defined by relational products, has recently been expanded to include a nonrelational offering with the addition of Azure Cosmos DB.

Overall experience and value: Reference customers gave Microsoft the highest score for overall experience with a vendor, as well as for value for money. Additionally, Microsoft scored above the average for end-user training and administration and management capabilities.

Cautions

Completeness of product suite: Thirty percentof Microsoft’s surveyed reference customers identified absent or weak functionality in its products. They pointed, for example, to weak tools for migrating on-premises workloads to Azure, shortcomings in the administration of distributed SQL Server instances, and lagging security features. Another issue they identified is the lack of parity between Microsoft’s on-premises tools, which are viewed as more robust, and the versions in Azure. Microsoft’s Azure SQL Database Managed Instance, which launched on 1 October 2018, should help address this disparity.

Pace of feature delivery: The pace of Microsoft’s feature delivery was a concern for many reference customers. Multiple reference customers stated that Microsoft is too focused on developing new features, rather than maturing existing capabilities. Others found it challenging to understand how disparate features were weaved into a cohesive story.

Challenges communicating hybrid vision: Reference customers repeatedly described Microsoft’s new features as ad hoc and fragmented, rather than as parts of an overall, holistic vision of a hybrid data management environment spanning on-premises and the cloud. Although Microsoft continues to build on its hybrid capabilities with features like transactional replication to SQL Server on Azure and the Azure Database Migration Service, it needs to do more to communicate a cohesive vision for hybrid deployment.

MongoDB

MongoDB, which is based in New York City, U.S., offers MongoDB Enterprise Advanced; MongoDB Enterprise for OEM; MongoDB Stitch, a managed “back end as a service”; MongoDB Atlas, a cloud-based dbPaaS offering; and MongoDB Mobile. Additionally, the company offers MongoDB Charts, a data visualization product currently in beta testing, as well as management tools and various connectors for business intelligence and analytics.

MongoDB did not respond to requests to participate in this research, to provide details of reference customers or to supply supplementary information. Therefore, Gartner’s analysis of MongoDB in this Magic Quadrant draws on credible public sources.

Strengths

Expanding product portfolio: MongoDB’s growing portfolio of offerings is well-positioned to satisfy its core market of developers. Components like Charts and its aggregation pipeline builder expand the usefulness of data stored in MongoDB, which previously had limited utility.

Growth in dbPaaS: Since its introduction in 2017, MongoDB claims Atlas has won over 4,400 customers (as of April 2018). Atlas includes a free tier and is offered in AWS, GCP and Microsoft Azure.

Developer mind share: MongoDB’s focused marketing efforts continue to attract significant mind share among developers and general interest in its product portfolio.

Cautions

Pricing and contract negotiation: Users of Gartner’s inquiry service regularly complain of price increases and inflexibility when negotiating contracts with MongoDB. It is common for customers to look for alternatives or to use the unsupported MongoDB Community Edition as a way to control costs.

Migration challenges: MongoDB positions its products as replacements for any DBMS product, but primarily those of incumbent RDBMS vendors and especially Oracle. Conversations with Gartner clients that have tried migrating complex applications indicate that they routinely encounter challenges to completing the migration.

Increasing competition: Since MongoDB helped define the NoSQL (now “nonrelational”) DBMS segment, dozens of competitors have emerged, ranging from large incumbents to fellow “insurgents.” MongoDB may have difficulty maintaining its competitive position as more established companies compete with the same marketing message of developer agility, supported by stronger technical foundations and better integration across portfolio components.

Oracle

Oracle, which is based in Redwood Shores, California, U.S., markets a complete set of DBMS products for operational systems. These include Oracle Database, Oracle TimesTen, Oracle Berkeley DB, Oracle NoSQL Database and MySQL. In addition to stand-alone software and cloud versions, several of Oracle’s DBMSs are available in engineered systems (appliances). Oracle recently released its Autonomous Transaction Processing (ATP) dbPaaS.

Strengths

Cloud innovation: Oracle has continued to innovate in the cloud by releasing its Autonomous Database. This is a major effort to incorporate ML into the management of not only Oracle Database but also other products, such as Oracle NoSQL, at all levels. By using ML techniques and underlying hardware, Oracle is able to tune databases automatically, update and patch the DBMS without downtime, and provide stronger DBMS security. This effort will reduce the routine tasks of a database administrator, while improving performance.

Customer loyalty, performance and functionality: Oracle has many longtime large customers, as is demonstrated by the survey of reference customers, with three-quarters having more than 1,000 licenses and well over half having used Oracle for more than eight to 10 years. Oracle received the highest score of any vendor in this Magic Quadrant for product capabilities, and 89% of Oracle’s surveyed reference customers chose it for its product functionality and performance.

Product satisfaction: Reference customers for Oracle scored it above average for both database security activity monitoring and HA/DR. In both categories, Oracle was the only vendor one STD above the mean.

Cautions

Cloud competition: With the notable exception of the Application Express (APEX) service, Oracle was late to the market with managed services (dbPaaS). It has now released a true dbPaaS in the form of ATP. However, adoption of Oracle Cloud has been predominantly by existing Oracle customers, whereas Oracle’s cloud competitors have customers from all DBMS vendors. For Oracle to compete in the public cloud sector, it will need to add managed services (dbPaaS) from its competitors. It must also end the practice of not certifying or changing the licensing metrics of the Oracle Database on competitors’ cloud platforms.

Negotiations and license complexity: Business practices remain an issue for Oracle, with contract negotiations scoring one STD below the mean. Clients who contact Gartner often accuse Oracle of having draconian licensing practices. Surveyed reference customers complained about Oracle’s cost, auditing practices and virtualization policies as major issues on-premises. Oracle continues to require double the number of licenses for using its cloud competitors, while reducing the available functionality. However, Oracle has made its cloud licensing more flexible by, for example, including bring your own licensing (BYOL) options to encourage customers to move to the cloud.

Support and patching challenges: Oracle received the lowest survey score of all vendors for service and support. This score is underlined by comments made by clients during Gartner interactions, which identify difficulty with patching, poor responses and the need for escalations. This has been an issue for Oracle for several years as the size of its customer base has grown. However, Gartner has seen service and support issues reduced as customers move to the cloud, where patching is automated or performed by Oracle directly.

SAP

SAP, which is based in Walldorf, Germany, offers several OPDBMS products: SAP Adaptive Server Enterprise (ASE), SAP SQL Anywhere and SAP HANA. SAP HANA is available as an appliance or as software only (as SAP HANA Tailored Datacenter Integration). Both SAP ASE and SAP HANA are available as cloud offerings, including SAP HANA as a Service.

Strengths

Continuing market leadership: SAP remains among the leaders in Gartner’s market share statistics for 2017, although its growth slowed to below the market rate. SAP HANA claims more than 25,000 customers as of July 2018 — over half of the SAP application installed base. SAP is stepping up its pursuit of general-purpose DBMS use cases with simplified pricing and changes of sales force focus, and expanding partner and ISV programs.

Market vision: SAP continued to pursue an aggressive vision in 2017 by enhancing its multimodel capabilities with document support, including text, geographical and spatial analytics. Gartner expects to see OrientDB technology (from newly acquired Callidus Software) reflected in future releases. SAP bundles numerous capabilities that are available from other vendors only at extra cost. Thus SAP HANA Enterprise Edition includes predictive and streaming analytics and innovative privacy capabilities. SAP’s aggressively communicated roadmap encompasses expanded deployment options, microservices, tool enhancements, data tiering and life cycle support.

Performance and integration enhancements: Surveyed SAP reference customers again praised SAP HANA’s performance, speed, and ability to combine transactions and analytics in the same database (hybrid transaction/analytical processing [HTAP]). There were also many appreciative comments about HANA’s seamless and well-supported migration capabilities — which are crucial, as most customers still migrate to HANA from existing DBMSs. SAP’s portfolio expanded in 2018 by enhancing SAP HANA with a Data Management Suite that includes data discovery, cleansing, governance and connections to third-party data.

Cautions

Perceived value for money: Despite recent aggressive pricing, bundling and packaging optimizations, surveyed SAP HANA reference customers scored SAP one STD below the median for both value and pricing method. Overcoming this perception will require continued work with existing and prospective customers to highlight SAP HANA’s pricing and packaging model and total cost of ownership, its superior data compression and minimal redundancy, included value-add features, and flexible packaging options.

Challenging usage experience: SAP’s HANA reference customer scores point to issues with ease of programming, quality of training and professional services. All of these are areas that have received significant investment (and a refreshed Enterprise Architecture Designer), but SAP has more work to do to communicate the improvements to customers.

Functionality gaps: SAP’s aggressive addition of SAP HANA features had prioritized support for its own applications. For general-purpose DBMS use, SAP HANA now needs additional capabilities to compete better, including write-capable replicas, Java stored procedures, and increased support for features in SQL 2003 and beyond.

獲得更多的PTT最新消息
按讚加入粉絲團