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DBMS > Apache Phoenix vs. Databend vs. jBASE vs. Spark SQL vs. VoltDB

System Properties Comparison Apache Phoenix vs. Databend vs. jBASE vs. Spark SQL vs. VoltDB

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatabend  Xexclude from comparisonjBASE  Xexclude from comparisonSpark SQL  Xexclude from comparisonVoltDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA robust multi-value DBMS comprising development tools and middlewareSpark 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 DBMSRelational DBMSMultivalue DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.47
Rank#157  Overall
#73  Relational DBMS
Websitephoenix.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
www.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasespark.apache.org/­sqlwww.voltdb.com
Technical documentationphoenix.apache.orgdocs.databend.comdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9spark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.voltdb.com
DeveloperApache Software FoundationDatabend LabsRocket Software (formerly Zumasys)Apache Software FoundationVoltDB Inc.
Initial release20142021199120142010
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.0.59, April 20235.73.5.0 ( 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 languageJavaRustScalaJava, C++
Server operating systemsLinux
Unix
Windows
hosted
Linux
macOS
AIX
Linux
Windows
Linux
OS X
Windows
Linux
OS X infofor development
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesoptionalyesyes
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.nonoyesno
Secondary indexesyesnonoyes
SQL infoSupport of SQLyesyesEmbedded SQL for jBASE in BASICSQL-like DML and DDL statementsyes infoonly a subset of SQL 99
APIs and other access methodsJDBCCLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
JavaScript (Node.js)
Python
Rust
.Net
Basic
Jabbascript
Java
Java
Python
R
Scala
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnoyesnoJava
Triggersnonoyesnono
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
noneyesnoneMulti-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 Consistency
Foreign keys infoReferential integritynonononono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDnoACID 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.yesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyUsers with fine-grained authorization concept, user rolesAccess rights can be defined down to the item levelnoUsers and roles with access to stored procedures

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More resources
Apache PhoenixDatabendjBASESpark SQLVoltDB
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