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DBMS > Infobright vs. Splice Machine vs. XTDB

System Properties Comparison Infobright vs. Splice Machine vs. XTDB

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Editorial information provided by DB-Engines
NameInfobright  Xexclude from comparisonSplice Machine  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionHigh performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.96
Rank#194  Overall
#91  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websiteignitetech.com/­softwarelibrary/­infobrightdbsplicemachine.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationsplicemachine.com/­how-it-workswww.xtdb.com/­docs
DeveloperIgnite Technologies Inc.; formerly InfoBright Inc.Splice MachineJuxt Ltd.
Initial release200520142019
Current release3.1, March 20211.19, September 2021
License infoCommercial or Open Sourcecommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open Source infoAGPL 3.0, commercial license availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaClojure
Server operating systemsLinux
Windows
Linux
OS X
Solaris
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, extensible-data-notation format
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.nono
Secondary indexesno infoKnowledge Grid Technology used insteadyesyes
SQL infoSupport of SQLyesyeslimited SQL, making use of Apache Calcite
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
HTTP REST
JDBC
Supported programming languages.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Clojure
Java
Server-side scripts infoStored proceduresnoyes infoJavano
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesAccess rights for users, groups and roles according to SQL-standard

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More resources
InfobrightSplice MachineXTDB infoformerly named Crux
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Ignite Buys Database Vendor Infobright
2 May 2017, Datanami

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Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
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Splice Machine Launches Feature Store to Simplify Feature Engineering
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