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DBMS > Bangdb vs. GigaSpaces vs. GridGain vs. SQream DB

System Properties Comparison Bangdb vs. GigaSpaces vs. GridGain vs. SQream DB

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGridGain  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsGridGain is an in-memory computing platform, built on Apache Ignitea GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial DBMSGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websitebangdb.comwww.gigaspaces.comwww.gridgain.comsqream.com
Technical documentationdocs.bangdb.comdocs.gigaspaces.com/­latest/­landing.htmlwww.gridgain.com/­docs/­index.htmldocs.sqream.com
DeveloperSachin Sinha, BangDBGigaspaces TechnologiesGridGain Systems, Inc.SQream Technologies
Initial release2012200020072017
Current releaseBangDB 2.0, October 202115.5, September 2020GridGain 8.5.12022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache Version 2; Commercial licenses availablecommercialcommercial
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, C++Java, C++, .NetJava, C++, .NetC++, CUDA, Haskell, Java, Scala
Server operating systemsLinuxLinux
macOS
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyes, ANSI Standard SQL Types
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 infoXML can be used for describing objects metadatayes
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesno
SQL infoSupport of SQLSQL like support with command line toolSQL-99 for query and DML statementsANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
.Net
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
.Net
C++
Java
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyesyes (compute grid and cache interceptors can be used instead)user defined functions in Python
Triggersyes, Notifications (with Streaming only)yes, event driven architectureyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardinghorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeyesyes
User concepts infoAccess controlyes (enterprise version only)Role-based access controlSecurity Hooks for custom implementations

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More resources
BangdbGigaSpacesGridGainSQream DB
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