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DBMS > Apache Pinot vs. Datomic vs. GeoSpock vs. Hypertable

System Properties Comparison Apache Pinot vs. Datomic vs. GeoSpock vs. Hypertable

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonDatomic  Xexclude from comparisonGeoSpock  Xexclude from comparisonHypertable  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilitySpatial and temporal data processing engine for extreme data scaleAn open source BigTable implementation based on distributed file systems such as Hadoop
Primary database modelRelational DBMSRelational DBMSRelational DBMSWide column store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Websitepinot.apache.orgwww.datomic.comgeospock.com
Technical documentationdocs.pinot.apache.orgdocs.datomic.com
DeveloperApache Software Foundation and contributorsCognitectGeoSpockHypertable Inc.
Initial release201520122009
Current release1.0.0, September 20231.0.6735, June 20232.0, September 20190.9.8.11, March 2016
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freecommercialOpen Source infoGNU version 3. 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, ClojureJava, JavascriptC++
Server operating systemsAll OS with a Java JDK11 or higherAll OS with a Java VMhostedLinux
OS X
Windows infoan inofficial Windows port is available
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nono
Secondary indexesyestemporal, categoricalrestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLSQL-like query languagenoANSI SQL for query only (using Presto)no
APIs and other access methodsJDBCRESTful HTTP APIJDBCC++ API
Thrift
Supported programming languagesGo
Java
Python
Clojure
Java
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction Functionsnono
TriggersBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnone infoBut extensive use of caching in the application peersAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersselectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentno
User concepts infoAccess controlnoAccess rights for users can be defined per tableno

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Apache PinotDatomicGeoSpockHypertable
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