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DBMS > HBase vs. Splice Machine vs. STSdb vs. TimescaleDB

System Properties Comparison HBase vs. Splice Machine vs. STSdb vs. TimescaleDB

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonSplice Machine  Xexclude from comparisonSTSdb  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionWide-column store based on Apache Hadoop and on concepts of BigTableOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelWide column storeRelational DBMSKey-value storeTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitehbase.apache.orgsplicemachine.comgithub.com/­STSSoft/­STSdb4www.timescale.com
Technical documentationhbase.apache.org/­book.htmlsplicemachine.com/­how-it-worksdocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetSplice MachineSTS Soft SCTimescale
Initial release2008201420112017
Current release2.3.4, January 20213.1, March 20214.0.8, September 20152.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoAGPL 3.0, commercial license availableOpen Source infoGPLv2, commercial 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 languageJavaJavaC#C
Server operating systemsLinux
Unix
Windows infousing Cygwin
Linux
OS X
Solaris
Windows
WindowsLinux
OS X
Windows
Data schemeschema-free, schema definition possibleyesyesyes
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesyes infoprimitive types and user defined types (classes)numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.noyes
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyesnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJava API
RESTful HTTP API
Thrift
JDBC
Native Spark Datasource
ODBC
.NET Client APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C#
Java
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infoCoprocessors in Javayes infoJavanouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar Partitioningnoneyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
noneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)ACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyes
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 (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
HBaseSplice MachineSTSdbTimescaleDB
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