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DBMS > Drizzle vs. Faircom EDGE vs. IBM Db2 vs. Splice Machine

System Properties Comparison Drizzle vs. Faircom EDGE vs. IBM Db2 vs. Splice Machine

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonSplice Machine  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsCommon in IBM host environments, 2 different versions for host and Windows/LinuxOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMS
Secondary database modelsDocument store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.03
Rank#380  Overall
#59  Key-value stores
#157  Relational DBMS
Score127.49
Rank#8  Overall
#5  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitewww.faircom.com/­products/­faircom-edgewww.ibm.com/­products/­db2splicemachine.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlwww.ibm.com/­docs/­en/­db2splicemachine.com/­how-it-works
DeveloperDrizzle project, originally started by Brian AkerFairCom CorporationIBMSplice Machine
Initial release200819791983 infohost version2014
Current release7.2.4, September 2012V3, October 202012.1, October 20163.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercial infoRestricted, free version availablecommercial infofree version is 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++ANSI C, C++C and C++Java
Server operating systemsFreeBSD
Linux
OS X
Android
Linux infoARM, x86
Raspbian
Windows
AIX
HP-UX
Linux
Solaris
Windows
z/OS
Linux
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyes
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.yes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsyes infoANSI SQL queriesyesyes
APIs and other access methodsJDBCADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Java
PHP
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yesyes infoJava
Triggersno infohooks for callbacks inside the server can be used.yesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningSharding infoonly with Windows/Unix/Linux VersionShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoSynchronous and asynchronous realtime replication based on transaction logsyes infowith separate tools (MQ, InfoSphere)Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyes infowhen using SQLyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes, 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.yesyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.fine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
DrizzleFaircom EDGE infoformerly c-treeEDGEIBM Db2 infoformerly named DB2 or IBM Database 2Splice Machine
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