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DBMS > Bangdb vs. FatDB vs. Ignite vs. Percona Server for MongoDB vs. Spark SQL

System Properties Comparison Bangdb vs. FatDB vs. Ignite vs. Percona Server for MongoDB vs. Spark SQL

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonFatDB  Xexclude from comparisonIgnite  Xexclude from comparisonPercona Server for MongoDB  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.
DescriptionConverged and high performance database for device data, events, time series, document and graphA .NET NoSQL DBMS that can integrate with and extend SQL Server.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A drop-in replacement for MongoDB Community Edition with enterprise-grade features.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document store
Key-value store
Key-value store
Relational DBMS
Document storeRelational DBMS
Secondary database modelsSpatial DBMS
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
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.52
Rank#254  Overall
#39  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitebangdb.comignite.apache.orgwww.percona.com/­mongodb/­software/­percona-server-for-mongodbspark.apache.org/­sql
Technical documentationdocs.bangdb.comapacheignite.readme.io/­docsdocs.percona.com/­percona-distribution-for-mongodbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSachin Sinha, BangDBFatCloudApache Software FoundationPerconaApache Software Foundation
Initial release20122012201520152014
Current releaseBangDB 2.0, October 2021Apache Ignite 2.63.4.10-2.10, November 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoApache 2.0Open Source infoGPL Version 2Open 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++, Java, .NetC++Scala
Server operating systemsLinuxWindowsLinux
OS X
Solaris
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyesyes
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.noyesnono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesyesno
SQL infoSupport of SQLSQL like support with command line toolno infoVia inetgration in SQL ServerANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
C#C#
C++
Java
PHP
Python
Ruby
Scala
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsyes (compute grid and cache interceptors can be used instead)JavaScriptno
Triggersyes, Notifications (with Streaming only)yes infovia applicationsyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)selectable replication factoryes (replicated cache)Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes (compute grid and hadoop accelerator)yes
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyesyes
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 infovia In-Memory Engineno
User concepts infoAccess controlyes (enterprise version only)no infoCan implement custom security layer via applicationsSecurity Hooks for custom implementationsAccess rights for users and rolesno

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More resources
BangdbFatDBIgnitePercona Server for MongoDBSpark SQL
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