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DBMS > Apache Phoenix vs. Immudb vs. Kinetica vs. Spark SQL vs. VoltDB

System Properties Comparison Apache Phoenix vs. Immudb vs. Kinetica vs. Spark SQL vs. VoltDB

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonImmudb  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonVoltDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAn open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.Fully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.31
Rank#295  Overall
#42  Key-value stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.47
Rank#157  Overall
#73  Relational DBMS
Websitephoenix.apache.orggithub.com/­codenotary/­immudb
immudb.io
www.kinetica.comspark.apache.org/­sqlwww.voltdb.com
Technical documentationphoenix.apache.orgdocs.immudb.iodocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.voltdb.com
DeveloperApache Software FoundationCodenotaryKineticaApache Software FoundationVoltDB Inc.
Initial release20142020201220142010
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.2.3, April 20227.1, August 20213.5.0 ( 2.13), September 202311.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC, C++ScalaJava, C++
Server operating systemsLinux
Unix
Windows
BSD
Linux
macOS
Solaris
Windows
z/OS
LinuxLinux
OS X
Windows
Linux
OS X infofor development
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 SQLyesSQL-like syntaxSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes infoonly a subset of SQL 99
APIs and other access methodsJDBCgRPC protocol
PostgreSQL wire protocol
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnouser defined functionsnoJava
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesnono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyesyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users and roles on table levelnoUsers and roles with access to stored procedures

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More resources
Apache PhoenixImmudbKineticaSpark SQLVoltDB
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