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DBMS > Apache Pinot vs. EventStoreDB vs. Microsoft Azure Table Storage vs. Splice Machine

System Properties Comparison Apache Pinot vs. EventStoreDB vs. Microsoft Azure Table Storage vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonEventStoreDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyIndustrial-strength, open-source database solution built from the ground up for event sourcing.A Wide Column Store for rapid development using massive semi-structured datasetsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSEvent StoreWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score1.10
Rank#179  Overall
#1  Event Stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitepinot.apache.orgwww.eventstore.comazure.microsoft.com/­en-us/­services/­storage/­tablessplicemachine.com
Technical documentationdocs.pinot.apache.orgdevelopers.eventstore.comsplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsEvent Store LimitedMicrosoftSplice Machine
Initial release2015201220122014
Current release1.0.0, September 202321.2, February 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourcecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsAll OS with a Java JDK11 or higherLinux
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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 methodsJDBCRESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
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 infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingACID
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 controlAccess rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache PinotEventStoreDBMicrosoft Azure Table StorageSplice Machine
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