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DBMS > Apache Phoenix vs. Badger vs. Hazelcast vs. Spark SQL vs. VoltDB

System Properties Comparison Apache Phoenix vs. Badger vs. Hazelcast vs. Spark SQL vs. VoltDB

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBadger  Xexclude from comparisonHazelcast  Xexclude from comparisonSpark SQL  Xexclude from comparisonVoltDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A widely adopted in-memory data gridSpark 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 storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.22
Rank#320  Overall
#47  Key-value stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.47
Rank#157  Overall
#73  Relational DBMS
Websitephoenix.apache.orggithub.com/­dgraph-io/­badgerhazelcast.comspark.apache.org/­sqlwww.voltdb.com
Technical documentationphoenix.apache.orggodoc.org/­github.com/­dgraph-io/­badgerhazelcast.org/­imdg/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.voltdb.com
DeveloperApache Software FoundationDGraph LabsHazelcastApache Software FoundationVoltDB Inc.
Initial release20142017200820142010
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.3.6, November 20233.5.0 ( 2.13), September 202311.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availableOpen 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

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Implementation languageJavaGoJavaScalaJava, C++
Server operating systemsLinux
Unix
Windows
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
OS X
Windows
Linux
OS X infofor development
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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 infothe object must implement a serialization strategyno
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLyesnoSQL-like query languageSQL-like DML and DDL statementsyes infoonly a subset of SQL 99
APIs and other access methodsJDBCJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnoyes infoEvent Listeners, Executor ServicesnoJava
Triggersnonoyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneyes infoReplicated MapnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencynoneImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynonononono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoone or two-phase-commit; repeatable reads; read commitednoACID 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.yesnoyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoRole-based access controlnoUsers and roles with access to stored procedures

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More resources
Apache PhoenixBadgerHazelcastSpark SQLVoltDB
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