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DBMS > IRONdb vs. JaguarDB vs. Oracle Berkeley DB vs. OushuDB vs. Splice Machine

System Properties Comparison IRONdb vs. JaguarDB vs. Oracle Berkeley DB vs. OushuDB vs. Splice Machine

Editorial information provided by DB-Engines
NameIRONdb  Xexclude from comparisonJaguarDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonOushuDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityPerformant, highly scalable DBMS for AI and IoT applicationsWidely used in-process key-value storeA 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 modelTime Series DBMSKey-value store
Vector DBMS
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#381  Overall
#59  Key-value stores
#13  Vector DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score0.10
Rank#355  Overall
#154  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.circonus.com/solutions/time-series-database/www.jaguardb.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.oushu.com/­product/­oushuDBsplicemachine.com
Technical documentationdocs.circonus.com/irondb/category/getting-startedwww.jaguardb.com/­support.htmldocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.oushu.com/­documentationsplicemachine.com/­how-it-works
DeveloperCirconus LLC.DataJaguar, Inc.Oracle infooriginally developed by Sleepycat, which was acquired by OracleOushuSplice Machine
Initial release2017201519942014
Current releaseV0.10.20, January 20183.3 July 202318.1.40, May 20204.0.1, August 20203.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoGPL V3.0Open Source infocommercial license availablecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++ infothe server part. Clients available in other languagesC, Java, C++ (depending on the Berkeley DB edition)Java
Server operating systemsLinuxLinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
LinuxLinux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyes infotext, numeric, histogramsyesnoyesyes
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.nonoyes infoonly with the Berkeley DB XML edition
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLSQL-like query language (Circonus Analytics Query Language: CAQL)A subset of ANSI SQL is implemented infobut no views, foreign keys, triggersyes infoSQL interfaced based on SQLite is availableFull-featured ANSI SQL supportyes
APIs and other access methodsHTTP APIJDBC
ODBC
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languages.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
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C
C++
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes, in Luanonoyesyes infoJava
Triggersnonoyes infoonly for the SQL APIyesyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic, metric affinity per nodeShardingnoneyesShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter awareMulti-source replicationSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoHadoop integrationYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 datanonoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, 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.nonoyesyes
User concepts infoAccess controlnorights management via user accountsnoKerberos, SSL and role based accessAccess rights for users, groups and roles according to SQL-standard

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More resources
IRONdbJaguarDBOracle Berkeley DBOushuDBSplice Machine
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