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DBMS > Bangdb vs. Geode vs. SiteWhere vs. Spark SQL

System Properties Comparison Bangdb vs. Geode vs. SiteWhere vs. Spark SQL

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGeode  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesM2M integration platform for persisting/querying time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Key-value storeTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score1.86
Rank#134  Overall
#24  Key-value stores
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitebangdb.comgeode.apache.orggithub.com/­sitewhere/­sitewherespark.apache.org/­sql
Technical documentationdocs.bangdb.comgeode.apache.org/­docssitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSachin Sinha, BangDBOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.SiteWhereApache Software Foundation
Initial release2012200220102014
Current releaseBangDB 2.0, October 20211.1, February 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaJavaScala
Server operating systemsLinuxAll OS with a Java VM infothe JDK (8 or later) is also requiredLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freepredefined schemeyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyes
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.nononono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialnonono
SQL infoSupport of SQLSQL like support with command line toolSQL-like query language (OQL)noSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol
RESTful HTTP API
Java Client API
Memcached protocol
RESTful HTTP API
HTTP RESTJDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
.Net
All JVM based languages
C++
Groovy
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsno
Triggersyes, Notifications (with Streaming only)yes infoCache Event Listenersno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding infobased on HBaseyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replicationselectable replication factor infobased on HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodenono
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 modeyesnono
User concepts infoAccess controlyes (enterprise version only)Access rights per client and object definableUsers with fine-grained authorization conceptno

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More resources
BangdbGeodeSiteWhereSpark SQL
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