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DBMS > Axibase vs. Badger vs. Spark SQL vs. Tkrzw

System Properties Comparison Axibase vs. Badger vs. Spark SQL vs. Tkrzw

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Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisonBadger  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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.Spark SQL is a component on top of 'Spark Core' for structured data processingA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelTime Series DBMSKey-value storeRelational DBMSKey-value store
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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websiteaxibase.com/­docs/­atsd/­financegithub.com/­dgraph-io/­badgerspark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAxibase CorporationDGraph LabsApache Software FoundationMikio Hirabayashi
Initial release2013201720142020
Current release155853.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoScalaC++
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
macOS
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes infoshort, integer, long, float, double, decimal, stringnoyesno
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.nononono
Secondary indexesnonono
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
Proprietary protocol (Network API)
RESTful HTTP API
JDBC
ODBC
Supported programming languagesGo
Java
PHP
Python
R
Ruby
GoJava
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyesnonono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonoyes infousing specific database classes
User concepts infoAccess controlnonono

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AxibaseBadgerSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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