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DBMS > Drizzle vs. Faircom DB vs. IBM Db2 warehouse vs. Spark SQL vs. Sphinx

System Properties Comparison Drizzle vs. Faircom DB vs. IBM Db2 warehouse vs. Spark SQL vs. Sphinx

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  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.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Cloud-based data warehousing serviceSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score1.37
Rank#160  Overall
#74  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.faircom.com/­products/­faircom-dbwww.ibm.com/­products/­db2/­warehousespark.apache.org/­sqlsphinxsearch.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperDrizzle project, originally started by Brian AkerFairCom CorporationIBMApache Software FoundationSphinx Technologies Inc.
Initial release20081979201420142001
Current release7.2.4, September 2012V12, November 20203.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercial infoRestricted, free version availablecommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ANSI C, C++ScalaC++
Server operating systemsFreeBSD
Linux
OS X
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,yesyesyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyesno
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 infoImport/export of XML data possibleno
Secondary indexesyesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLyes infowith proprietary extensionsyes, ANSI SQL with proprietary extensionsyesSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsJDBCADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
.NET Client API
JDBC
ODBC
OLE DB
JDBC
ODBC
Proprietary protocol
Supported programming languagesC
C++
Java
PHP
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++PL/SQL, SQL PLnono
Triggersno infohooks for callbacks inside the server can be used.yesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integrityyesyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPFine grained access rights according to SQL-standard with additional protections for filesfine grained access rights according to SQL-standardnono

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More resources
DrizzleFaircom DB infoformerly c-treeACEIBM Db2 warehouse infoformerly named IBM dashDBSpark SQLSphinx
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