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DBMS > Apache Impala vs. HarperDB vs. Hive vs. KeyDB

System Properties Comparison Apache Impala vs. HarperDB vs. Hive vs. KeyDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHarperDB  Xexclude from comparisonHive  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.data warehouse software for querying and managing large distributed datasets, built on HadoopAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelRelational DBMSDocument storeRelational DBMSKey-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.71
Rank#226  Overall
#33  Key-value stores
Websiteimpala.apache.orgwww.harperdb.iohive.apache.orggithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationimpala.apache.org/­impala-docs.htmldocs.harperdb.io/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.keydb.dev
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHarperDBApache Software Foundation infoinitially developed by FacebookEQ Alpha Technology Ltd.
Initial release2013201720122019
Current release4.1.0, June 20223.1, August 20213.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree community edition availableOpen Source infoApache Version 2Open Source infoBSD-3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Node.jsJavaC++
Server operating systemsLinuxLinux
OS X
All OS with a Java VMLinux
Data schemeyesdynamic schemayesschema-free
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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 indexesyesyesyesyes infoby using the Redis Search module
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like data manipulation statementsSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Thrift
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++
Java
PHP
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceCustom Functions infosince release 3.1yes infouser defined functions and integration of map-reduceLua
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infothe nodes on which a table resides can be definedselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnoOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
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 KerberosAccess rights for users and rolesAccess rights for users, groups and rolessimple password-based access control and ACL

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More resources
Apache ImpalaHarperDBHiveKeyDB
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