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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDragonfly  Xexclude from comparisonHarperDB  Xexclude from comparisonHive  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 instanceUltra-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 Hadoop
Primary database modelRelational DBMSKey-value storeDocument storeRelational DBMS
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
Score0.41
Rank#266  Overall
#38  Key-value stores
Score0.55
Rank#248  Overall
#38  Document stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websiteimpala.apache.orggithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.harperdb.iohive.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmlwww.dragonflydb.io/­docsdocs.harperdb.io/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDragonflyDB team and community contributorsHarperDBApache Software Foundation infoinitially developed by Facebook
Initial release2013202320172012
Current release4.1.0, June 20221.0, March 20233.1, August 20213.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBSL 1.1commercial infofree community edition availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Node.jsJava
Server operating systemsLinuxLinuxLinux
OS X
All OS with a Java VM
Data schemeyesscheme-freedynamic schemayes
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyes infoJSON data typesyes
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 indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like data manipulation statementsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Proprietary protocol infoRESP - REdis Serialization ProtocolJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Thrift
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
.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
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceLuaCustom Functions infosince release 3.1yes infouser defined functions and integration of map-reduce
Triggersnopublish/subscribe channels provide some trigger functionalitynono
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyes infothe nodes on which a table resides can be definedselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of command blocks and scriptsAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
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 KerberosPassword-based authenticationAccess rights for users and rolesAccess rights for users, groups and roles

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More resources
Apache ImpalaDragonflyHarperDBHive
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