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DBMS > Bangdb vs. Databricks vs. GigaSpaces vs. HBase vs. Sequoiadb

System Properties Comparison Bangdb vs. Databricks vs. GigaSpaces vs. HBase vs. Sequoiadb

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDatabricks  Xexclude from comparisonGigaSpaces  Xexclude from comparisonHBase  Xexclude from comparisonSequoiadb  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsWide-column store based on Apache Hadoop and on concepts of BigTableNewSQL database with distributed OLTP and SQL
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document store
Relational DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Wide column storeDocument store
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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitebangdb.comwww.databricks.comwww.gigaspaces.comhbase.apache.orgwww.sequoiadb.com
Technical documentationdocs.bangdb.comdocs.databricks.comdocs.gigaspaces.com/­latest/­landing.htmlhbase.apache.org/­book.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperSachin Sinha, BangDBDatabricksGigaspaces TechnologiesApache Software Foundation infoApache top-level project, originally developed by PowersetSequoiadb Ltd.
Initial release20122013200020082013
Current releaseBangDB 2.0, October 202115.5, September 20202.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache version 2Open Source infoServer: AGPL; Client: Apache V2
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++, .NetJavaC++
Server operating systemsLinuxhostedLinux
macOS
Solaris
Windows
Linux
Unix
Windows infousing Cygwin
Linux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesoptions to bring your own types, AVROyes infooid, date, timestamp, binary, regex
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.noyesno infoXML can be used for describing objects metadatanono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesnoyes
SQL infoSupport of SQLSQL like support with command line toolwith Databricks SQLSQL-99 for query and DML statementsnoSQL-like query language
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSON
Supported programming languagesC
C#
C++
Java
Python
Python
R
Scala
.Net
C++
Java
Python
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyesyes infoCoprocessors in JavaJavaScript
Triggersyes, Notifications (with Streaming only)yes, event driven architectureyesno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDSingle row ACID (across millions of columns)Document is locked during a transaction
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 modenoyesyesno
User concepts infoAccess controlyes (enterprise version only)Role-based access controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access control
More information provided by the system vendor
BangdbDatabricksGigaSpacesHBaseSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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