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DBMS > Dragonfly vs. FatDB vs. Informix vs. Ingres vs. Spark SQL

System Properties Comparison Dragonfly vs. FatDB vs. Informix vs. Ingres vs. Spark SQL

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonFatDB  Xexclude from comparisonInformix  Xexclude from comparisonIngres  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceA .NET NoSQL DBMS that can integrate with and extend SQL Server.A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataWell established RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument store
Key-value store
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score17.87
Rank#35  Overall
#22  Relational DBMS
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.ibm.com/­products/­informixwww.actian.com/­databases/­ingresspark.apache.org/­sql
Technical documentationwww.dragonflydb.io/­docsinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
docs.actian.com/­ingresspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDragonflyDB team and community contributorsFatCloudIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Actian CorporationApache Software Foundation
Initial release2023201219841974 infooriginally developed at University Berkely in early 1970s2014
Current release1.0, March 202314.10.FC5, November 202011.2, May 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialcommercial infofree developer edition availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#C, C++ and JavaCScala
Server operating systemsLinuxWindowsAIX
HP-UX
Linux
macOS
Solaris
Windows
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Data schemescheme-freeschema-freeyesyesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyes infoSince Version 12.10 support for JSON/BSON datatypesyesyes
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 infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnono infoVia inetgration in SQL ServeryesyesSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization Protocol.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
ODBC
Supported programming languagesC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C#.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresLuayes infovia applicationsyesyesno
Triggerspublish/subscribe channels provide some trigger functionalityyes infovia applicationsyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replication
Source-replica replication
Ingres Replicatornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyes infoMVCCyes
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.yesyesnono
User concepts infoAccess controlPassword-based authenticationno infoCan implement custom security layer via applicationsUsers with fine-grained authentication, authorization, and auditing controlsfine grained access rights according to SQL-standardno

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More resources
DragonflyFatDBInformixIngresSpark SQL
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