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DBMS > Ignite vs. IRONdb vs. Oracle Berkeley DB vs. Splice Machine

System Properties Comparison Ignite vs. IRONdb vs. Oracle Berkeley DB vs. Splice Machine

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Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonIRONdb  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSplice Machine  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityWidely used in-process key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value store
Relational DBMS
Time Series DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteignite.apache.orgwww.circonus.com/solutions/time-series-database/www.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsplicemachine.com
Technical documentationapacheignite.readme.io/­docsdocs.circonus.com/irondb/category/getting-starteddocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsplicemachine.com/­how-it-works
DeveloperApache Software FoundationCirconus LLC.Oracle infooriginally developed by Sleepycat, which was acquired by OracleSplice Machine
Initial release2015201719942014
Current releaseApache Ignite 2.6V0.10.20, January 201818.1.40, May 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infocommercial license availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetC and C++C, Java, C++ (depending on the Berkeley DB edition)Java
Server operating systemsLinux
OS X
Solaris
Windows
LinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsnoyes
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.yesnoyes infoonly with the Berkeley DB XML edition
Secondary indexesyesnoyesyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSQL-like query language (Circonus Analytics Query Language: CAQL)yes infoSQL interfaced based on SQLite is availableyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
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++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)yes, in Luanoyes infoJava
Triggersyes (cache interceptors and events)noyes infoonly for the SQL APIyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)configurable replication factor, datacenter awareSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlSecurity Hooks for custom implementationsnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
IgniteIRONdbOracle Berkeley DBSplice Machine
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