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DBMS > Bangdb vs. Firebase Realtime Database vs. GigaSpaces vs. Hypertable vs. Spark SQL

System Properties Comparison Bangdb vs. Firebase Realtime Database vs. GigaSpaces vs. Hypertable vs. Spark SQL

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGigaSpaces  Xexclude from comparisonHypertable  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionConverged and high performance database for device data, events, time series, document and graphCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsAn open source BigTable implementation based on distributed file systems such as HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document storeDocument store
Object oriented DBMS infoValues are user defined objects
Wide column storeRelational 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
Score14.29
Rank#39  Overall
#6  Document stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitebangdb.comfirebase.google.com/­products/­realtime-databasewww.gigaspaces.comspark.apache.org/­sql
Technical documentationdocs.bangdb.comfirebase.google.com/­docs/­databasedocs.gigaspaces.com/­latest/­landing.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSachin Sinha, BangDBGoogle infoacquired by Google 2014Gigaspaces TechnologiesHypertable Inc.Apache Software Foundation
Initial release20122012200020092014
Current releaseBangDB 2.0, October 202115.5, September 20200.9.8.11, March 20163.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++Java, C++, .NetC++Scala
Server operating systemsLinuxhostedLinux
macOS
Solaris
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesnoyes
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.nonono infoXML can be used for describing objects metadatano
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesrestricted infoonly exact value or prefix value scansno
SQL infoSupport of SQLSQL like support with command line toolnoSQL-99 for query and DML statementsnoSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
C++ API
Thrift
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
Java
JavaScript
Objective-C
.Net
C++
Java
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'yesnono
Triggersyes, Notifications (with Streaming only)Callbacks are triggered when data changesyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardingyes, utilizing Spark Core
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
selectable replication factor on file system levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoMap-Reduce pattern can be built with XAP task executorsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDnono
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 modeyesno
User concepts infoAccess controlyes (enterprise version only)yes, based on authentication and database rulesRole-based access controlnono

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More resources
BangdbFirebase Realtime DatabaseGigaSpacesHypertableSpark SQL
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