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DBMS > FatDB vs. GigaSpaces vs. Ingres vs. Spark SQL

System Properties Comparison FatDB vs. GigaSpaces vs. Ingres vs. Spark SQL

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGigaSpaces  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 .NET NoSQL DBMS that can integrate with and extend SQL Server.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsWell established RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#175  Overall
#30  Document stores
#6  Object oriented DBMS
Score6.10
Rank#69  Overall
#38  Relational DBMS
Score22.86
Rank#35  Overall
#21  Relational DBMS
Websitewww.gigaspaces.comwww.actian.com/­data-management/­ingres-sql-rdbmsspark.apache.org/­sql
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.actian.com/­ingresspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudGigaspaces TechnologiesActian CorporationApache Software Foundation
Initial release201220001974 infooriginally developed at University Berkely in early 1970s2014
Current release15.5, September 202011.0, April 20173.2.0, October 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#Java, C++, .NetCScala
Server operating systemsWindowsLinux
macOS
Solaris
Windows
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.no infoXML can be used for describing objects metadatano infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-99 for query and DML statementsyesSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
ODBC
Supported programming languagesC#.Net
C++
Java
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyesyesno
Triggersyes infovia applicationsyes, event driven architectureyesno
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 nodesselectable replication factorMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Ingres Replicatornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoMap-Reduce pattern can be built with XAP task executorsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyes
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.yesnono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsRole-based access controlfine grained access rights according to SQL-standardno
More information provided by the system vendor
FatDBGigaSpacesIngresSpark SQL
Specific characteristicsGigaSpaces, the pioneer of In-Memory Computing , drives enterprise digital transformation...
» more
Competitive advantages​ AI Driven Autonomous Operations – GigaSpaces’ unique AI driven technology simplifies...
» more
Typical application scenariosApplication Acceleration, Smart Caching, BI Acceleration on Fresh Data, Digital Integration...
» more
Key customersMorgan Stanley, Bank of America, Goldman Sachs, PriceRunner, Cerner, Societe Generale,...
» more
Market metricsForrester has positioned GigaSpaces as a strong performer in The Forrester Wave™:...
» more
Licensing and pricing modelsGigaSpaces offers both open source and commercial editions with annual subscriptions....
» more

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3rd partiesSQLFlow: Provides a visual representation of the overall flow of data. Automated SQL data lineage analysis across Databases, ETL, Business Intelligence, Cloud and Hadoop environments by parsing SQL Script and stored procedure.
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More resources
FatDBGigaSpacesIngresSpark SQL
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