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DBMS > Apache Impala vs. Badger vs. Dragonfly vs. Kinetica vs. TimescaleDB

System Properties Comparison Apache Impala vs. Badger vs. Dragonfly vs. Kinetica vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBadger  Xexclude from comparisonDragonfly  Xexclude from comparisonKinetica  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceFully vectorized database across both GPUs and CPUsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSKey-value storeKey-value storeRelational DBMSTime Series DBMS
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.49
Rank#261  Overall
#38  Key-value stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websiteimpala.apache.orggithub.com/­dgraph-io/­badgergithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.kinetica.comwww.timescale.com
Technical documentationimpala.apache.org/­impala-docs.htmlgodoc.org/­github.com/­dgraph-io/­badgerwww.dragonflydb.io/­docsdocs.kinetica.comdocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDGraph LabsDragonflyDB team and community contributorsKineticaTimescale
Initial release20132017202320122017
Current release4.1.0, June 20221.0, March 20237.1, August 20212.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoBSL 1.1commercialOpen 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 languageC++GoC++C, C++C
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
LinuxLinuxLinux
OS X
Windows
Data schemeyesschema-freescheme-freeyesyes
Typing infopredefined data types such as float or dateyesnostrings, hashes, lists, sets, sorted sets, bit arraysyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonononoyes
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
Proprietary protocol infoRESP - REdis Serialization ProtocolJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBCGoC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoLuauser defined functionsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonopublish/subscribe channels provide some trigger functionalityyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-replica replicationSource-replica replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic execution of command blocks and scriptsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, strict serializability by the serveryesyes
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.nonoyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoPassword-based authenticationAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
Apache ImpalaBadgerDragonflyKineticaTimescaleDB
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