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DBMS > Apache Phoenix vs. Datomic vs. FatDB vs. Microsoft Azure Table Storage vs. Yaacomo

System Properties Comparison Apache Phoenix vs. Datomic vs. FatDB vs. Microsoft Azure Table Storage vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatomic  Xexclude from comparisonFatDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonYaacomo  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA .NET NoSQL DBMS that can integrate with and extend SQL Server.A Wide Column Store for rapid development using massive semi-structured datasetsOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSDocument store
Key-value store
Wide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Websitephoenix.apache.orgwww.datomic.comazure.microsoft.com/­en-us/­services/­storage/­tablesyaacomo.com
Technical documentationphoenix.apache.orgdocs.datomic.com
DeveloperApache Software FoundationCognitectFatCloudMicrosoftQ2WEB GmbH
Initial release20142012201220122009
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.0.7075, December 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureC#
Server operating systemsLinux
Unix
Windows
All OS with a Java VMWindowshostedAndroid
Linux
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyesnono infoVia inetgration in SQL Servernoyes
APIs and other access methodsJDBCRESTful HTTP API.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
RESTful HTTP APIJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Clojure
Java
C#.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsyes infoTransaction Functionsyes infovia applicationsno
TriggersnoBy using transaction functionsyes infovia applicationsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none infoBut extensive use of caching in the application peersselectable replication factoryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentnoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynono infoCan implement custom security layer via applicationsAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard

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More resources
Apache PhoenixDatomicFatDBMicrosoft Azure Table StorageYaacomo
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