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DBMS > Apache Impala vs. Hive vs. IBM Db2 Event Store vs. Percona Server for MongoDB vs. Splice Machine

System Properties Comparison Apache Impala vs. Hive vs. IBM Db2 Event Store vs. Percona Server for MongoDB vs. Splice Machine

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHive  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for Hadoopdata warehouse software for querying and managing large distributed datasets, built on HadoopDistributed Event Store optimized for Internet of Things use casesA drop-in replacement for MongoDB Community Edition with enterprise-grade features.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSEvent Store
Time Series DBMS
Document storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.60
Rank#246  Overall
#39  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteimpala.apache.orghive.apache.orgwww.ibm.com/­products/­db2-event-storewww.percona.com/­mongodb/­software/­percona-server-for-mongodbsplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homewww.ibm.com/­docs/­en/­db2-event-storedocs.percona.com/­percona-distribution-for-mongodbsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation infoinitially developed by FacebookIBMPerconaSplice Machine
Initial release20132012201720152014
Current release4.1.0, June 20223.1.3, April 20222.03.4.10-2.10, November 20173.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2commercial infofree developer edition availableOpen Source infoGPL Version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC and C++C++Java
Server operating systemsLinuxAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinuxLinux
OS X
Solaris
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes infothrough the embedded Spark runtimenoyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
proprietary protocol using JSONJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
PHP
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infouser defined functions and integration of map-reduceyesJavaScriptyes infoJava
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorActive-active shard replicationSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infoquery execution via MapReducenoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infovia In-Memory Engineyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and rolesfine grained access rights according to SQL-standardAccess rights for users and rolesAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaHiveIBM Db2 Event StorePercona Server for MongoDBSplice Machine
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