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DBMS > Apache Phoenix vs. Datomic vs. Oracle Berkeley DB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Datomic vs. Oracle Berkeley DB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatomic  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparison
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 durabilityWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.datomic.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sql
Technical documentationphoenix.apache.orgdocs.datomic.comdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationCognitectOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software Foundation
Initial release2014201219942014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.0.6735, June 202318.1.40, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freeOpen Source infocommercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureC, Java, C++ (depending on the Berkeley DB edition)Scala
Server operating systemsLinux
Unix
Windows
All OS with a Java VMAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nonoyes infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesnoyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statements
APIs and other access methodsJDBCRESTful HTTP APIJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Clojure
Java
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infoTransaction Functionsnono
TriggersnoBy using transaction functionsyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none infoBut extensive use of caching in the application peersSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
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 developmentyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynonono

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More resources
Apache PhoenixDatomicOracle Berkeley DBSpark SQL
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