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DBMS > Apache Impala vs. Badger vs. Datomic vs. Hypertable vs. Kdb

System Properties Comparison Apache Impala vs. Badger vs. Datomic vs. Hypertable vs. Kdb

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBadger  Xexclude from comparisonDatomic  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.
DescriptionAnalytic DBMS for HadoopAn 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 durabilityAn open source BigTable implementation based on distributed file systems such as HadoopHigh performance Time Series DBMS
Primary database modelRelational DBMSKey-value storeRelational DBMSWide column storeTime Series DBMS
Vector DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Websiteimpala.apache.orggithub.com/­dgraph-io/­badgerwww.datomic.comkx.com
Technical documentationimpala.apache.org/­impala-docs.htmlgodoc.org/­github.com/­dgraph-io/­badgerdocs.datomic.comcode.kx.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDGraph LabsCognitectHypertable Inc.Kx Systems, a division of First Derivatives plc
Initial release20132017201220092000 infokdb was released 2000, kdb+ in 2003
Current release4.1.0, June 20221.0.6735, June 20230.9.8.11, March 20163.6, May 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercial infolimited edition freeOpen 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

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Implementation languageC++GoJava, ClojureC++q
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesnoyes
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 indexesyesnoyesrestricted infoonly exact value or prefix value scansyes infotable attribute 'grouped'
SQL infoSupport of SQLSQL-like DML and DDL statementsnononoSQL-like query language (q)
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIC++ API
Thrift
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBCGoClojure
Java
C++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infoTransaction Functionsnouser defined functions
TriggersnonoBy using transaction functionsnoyes infowith views
Partitioning methods infoMethods for storing different data on different nodesShardingnonenone infoBut extensive use of caching in the application peersShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenone infoBut extensive use of caching in the application peersselectable replication factor on file system levelSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyesno infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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.nonoyes inforecommended only for testing and developmentyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnononorights management via user accounts
More information provided by the system vendor
Apache ImpalaBadgerDatomicHypertableKdb
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...
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Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
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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...
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Licensing and pricing modelsupon request
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Apache ImpalaBadgerDatomicHypertableKdb
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