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DBMS > Apache Impala vs. Dragonfly vs. Kinetica

System Properties Comparison Apache Impala vs. Dragonfly vs. Kinetica

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDragonfly  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA 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 CPUs
Primary database modelRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.41
Rank#266  Overall
#38  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteimpala.apache.orggithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.kinetica.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.dragonflydb.io/­docsdocs.kinetica.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDragonflyDB team and community contributorsKinetica
Initial release201320232012
Current release4.1.0, June 20221.0, March 20237.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBSL 1.1commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C, C++
Server operating systemsLinuxLinuxLinux
Data schemeyesscheme-freeyes
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyes
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.nonono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Proprietary protocol infoRESP - REdis Serialization ProtocolJDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
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
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceLuauser defined functions
Triggersnopublish/subscribe channels provide some trigger functionalityyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of command blocks and scriptsno
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPassword-based authenticationAccess rights for users and roles on table level

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More resources
Apache ImpalaDragonflyKinetica
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