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DBMS > Apache Impala vs. HEAVY.AI vs. Riak KV vs. Typesense

System Properties Comparison Apache Impala vs. HEAVY.AI vs. Riak KV vs. Typesense

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonRiak KV  Xexclude from comparisonTypesense  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareDistributed, fault tolerant key-value storeA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelRelational DBMSRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesSearch engine
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score3.84
Rank#76  Overall
#9  Key-value stores
Score0.80
Rank#209  Overall
#14  Search engines
Websiteimpala.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
typesense.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.heavy.aiwww.tiot.jp/­riak-docs/­riak/­kv/­latesttypesense.org/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHEAVY.AI, Inc.OpenSource, formerly Basho Technologies
Initial release2013201620092015
Current release4.1.0, June 20225.10, January 20223.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2; enterprise edition availableOpen Source infoApache version 2, commercial enterprise editionOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++ and CUDAErlangC++
Server operating systemsLinuxLinuxLinux
OS X
Linux
Data schemeyesyesschema-freeschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesnorestrictedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnono
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Thrift
Vega
HTTP API
Native Erlang Interface
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/Thrift
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoErlangno
Triggersnonoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationselectable replication factorMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardyes, using Riak Security

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More resources
Apache ImpalaHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Riak KVTypesense
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