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

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

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDatabricks  Xexclude from comparisonGreenplum  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.Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Wide-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
Relational DBMSWide column storeDocument store
Relational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial 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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitebangdb.comwww.databricks.comgreenplum.orghbase.apache.orgwww.sequoiadb.com
Technical documentationdocs.bangdb.comdocs.databricks.comdocs.greenplum.orghbase.apache.org/­book.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperSachin Sinha, BangDBDatabricksPivotal Software Inc.Apache Software Foundation infoApache top-level project, originally developed by PowersetSequoiadb Ltd.
Initial release20122013200520082013
Current releaseBangDB 2.0, October 20217.0.0, September 20232.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoApache 2.0Open 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++JavaC++
Server operating systemsLinuxhostedLinuxLinux
Unix
Windows infousing Cygwin
Linux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-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.noyesyes infosince Version 4.2nono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesnoyes
SQL infoSupport of SQLSQL like support with command line toolwith Databricks SQLyesnoSQL-like query language
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSON
Supported programming languagesC
C#
C++
Java
Python
Python
R
Scala
C
Java
Perl
Python
R
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)yesyesno
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)yesSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
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 modenonoyesno
User concepts infoAccess controlyes (enterprise version only)fine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access control
More information provided by the system vendor
BangdbDatabricksGreenplumHBaseSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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