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DBMS > Badger vs. Datomic vs. HBase vs. Hypertable vs. Kdb

System Properties Comparison Badger vs. Datomic vs. HBase vs. Hypertable vs. Kdb

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatomic  Xexclude from comparisonHBase  Xexclude from comparisonHypertable  Xexclude from comparisonKdb  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityWide-column store based on Apache Hadoop and on concepts of BigTableAn open source BigTable implementation based on distributed file systems such as HadoopHigh performance Time Series DBMS
Primary database modelKey-value storeRelational DBMSWide column storeWide column storeTime Series DBMS
Vector DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Websitegithub.com/­dgraph-io/­badgerwww.datomic.comhbase.apache.orgkx.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.datomic.comhbase.apache.org/­book.htmlcode.kx.com
DeveloperDGraph LabsCognitectApache Software Foundation infoApache top-level project, originally developed by PowersetHypertable Inc.Kx Systems, a division of First Derivatives plc
Initial release20172012200820092000 infokdb was released 2000, kdb+ in 2003
Current release1.0.6735, June 20232.3.4, January 20210.9.8.11, March 20163.6, May 2018
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infolimited edition freeOpen Source infoApache version 2Open Source infoGNU version 3. Commercial license availablecommercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava, ClojureJavaC++q
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or datenoyesoptions to bring your own types, AVROnoyes
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
Secondary indexesnoyesnorestricted infoonly exact value or prefix value scansyes infotable attribute 'grouped'
SQL infoSupport of SQLnonononoSQL-like query language (q)
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP API
Thrift
C++ API
Thrift
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesGoClojure
Java
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyes infoCoprocessors in Javanouser defined functions
TriggersnoBy using transaction functionsyesnoyes infowith views
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
selectable replication factor on file system levelSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyesno infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDSingle row ACID (across millions of columns)nono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlnonoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnorights management via user accounts
More information provided by the system vendor
BadgerDatomicHBaseHypertableKdb
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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BadgerDatomicHBaseHypertableKdb
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