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DBMS > Apache Pinot vs. OpenTSDB vs. Splice Machine

System Properties Comparison Apache Pinot vs. OpenTSDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonOpenTSDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyScalable Time Series DBMS based on HBaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score1.68
Rank#142  Overall
#12  Time Series DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitepinot.apache.orgopentsdb.netsplicemachine.com
Technical documentationdocs.pinot.apache.orgopentsdb.net/­docs/­build/­html/­index.htmlsplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorscurrently maintained by Yahoo and other contributorsSplice Machine
Initial release201520112014
Current release1.0.0, September 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoLGPLOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsAll OS with a Java JDK11 or higherLinux
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnumeric data for metrics, strings for tagsyes
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.no
Secondary indexesnoyes
SQL infoSupport of SQLSQL-like query languagenoyes
APIs and other access methodsJDBCHTTP API
Telnet API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
Python
Erlang
Go
Java
Python
R
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoJava
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infobased on HBaseShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infobased on HBaseImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache PinotOpenTSDBSplice Machine
DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
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