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DBMS > Apache Impala vs. IRONdb vs. JaguarDB vs. OushuDB vs. Splice Machine

System Properties Comparison Apache Impala vs. IRONdb vs. JaguarDB vs. OushuDB vs. Splice Machine

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonIRONdb  Xexclude from comparisonJaguarDB  Xexclude from comparisonOushuDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityPerformant, highly scalable DBMS for AI and IoT applicationsA data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learningOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSKey-value store
Vector DBMS
Relational DBMSRelational 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
Score0.06
Rank#381  Overall
#59  Key-value stores
#13  Vector DBMS
Score0.10
Rank#355  Overall
#154  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteimpala.apache.orgwww.circonus.com/solutions/time-series-database/www.jaguardb.comwww.oushu.com/­product/­oushuDBsplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.circonus.com/irondb/category/getting-startedwww.jaguardb.com/­support.htmlwww.oushu.com/­documentationsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCirconus LLC.DataJaguar, Inc.OushuSplice Machine
Initial release2013201720152014
Current release4.1.0, June 2022V0.10.20, January 20183.3 July 20234.0.1, August 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGPL V3.0commercialOpen 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++C and C++C++ infothe server part. Clients available in other languagesJava
Server operating systemsLinuxLinuxLinuxLinuxLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyesyes
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 indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)A subset of ANSI SQL is implemented infobut no views, foreign keys, triggersFull-featured ANSI SQL supportyes
APIs and other access methodsJDBC
ODBC
HTTP APIJDBC
ODBC
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C
C++
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in Luanoyesyes infoJava
Triggersnononoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingyesShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awareMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoHadoop integrationYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnorights management via user accountsKerberos, SSL and role based accessAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaIRONdbJaguarDBOushuDBSplice Machine
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