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DBMS > Axibase vs. Badger vs. HEAVY.AI vs. PostgreSQL vs. Spark SQL

System Properties Comparison Axibase vs. Badger vs. HEAVY.AI vs. PostgreSQL vs. Spark SQL

Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisonBadger  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSKey-value storeRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS
Secondary database modelsSpatial DBMSDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.35
Rank#282  Overall
#25  Time Series DBMS
Score0.22
Rank#320  Overall
#47  Key-value stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaxibase.com/­docs/­atsd/­financegithub.com/­dgraph-io/­badgergithub.com/­heavyai/­heavydb
www.heavy.ai
www.postgresql.orgspark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.heavy.aiwww.postgresql.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAxibase CorporationDGraph LabsHEAVY.AI, Inc.PostgreSQL Global Development Group infowww.postgresql.org/­developerApache Software Foundation
Initial release2013201720161989 info1989: Postgres, 1996: PostgreSQL2014
Current release155855.10, January 202216.3, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidOpen Source infoApache 2.0Open Source infoApache Version 2; enterprise edition availableOpen Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoC++ and CUDACScala
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
LinuxFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes infoshort, integer, long, float, double, decimal, stringnoyesyesyes
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.nononoyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesnononoyesno
SQL infoSupport of SQLSQL-like query languagenoyesyes infostandard with numerous extensionsSQL-like DML and DDL statements
APIs and other access methodsJDBC
Proprietary protocol (Network API)
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesGo
Java
PHP
Python
R
Ruby
GoAll languages supporting JDBC/ODBC/Thrift
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnonouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersyesnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoRound robinpartitioning by range, list and (since PostgreSQL 11) by hashyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-source replicationSource-replica replication infoother methods possible by using 3rd party extensionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
AxibaseBadgerHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022PostgreSQLSpark SQL
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