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DBMS > Databricks vs. HBase vs. Sequoiadb vs. Tkrzw vs. VoltDB

System Properties Comparison Databricks vs. HBase vs. Sequoiadb vs. Tkrzw vs. VoltDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonSequoiadb  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonVoltDB  Xexclude from comparison
DescriptionThe 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.Wide-column store based on Apache Hadoop and on concepts of BigTableNewSQL database with distributed OLTP and SQLA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelDocument store
Relational DBMS
Wide column storeDocument store
Relational DBMS
Key-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Score1.44
Rank#158  Overall
#73  Relational DBMS
Websitewww.databricks.comhbase.apache.orgwww.sequoiadb.comdbmx.net/­tkrzwwww.voltdb.com
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=indexdocs.voltdb.com
DeveloperDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetSequoiadb Ltd.Mikio HirabayashiVoltDB Inc.
Initial release20132008201320202010
Current release2.3.4, January 20210.9.3, August 202011.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoServer: AGPL; Client: Apache V2Open Source infoApache Version 2.0Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++Java, C++
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
LinuxLinux
macOS
Linux
OS X infofor development
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleschema-freeschema-freeyes
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyes infooid, date, timestamp, binary, regexnoyes
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.yesnonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query languagenoyes infoonly a subset of SQL 99
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSONJava API
JDBC
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C++
Java
PHP
Python
C++
Java
Python
Ruby
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoCoprocessors in JavaJavaScriptnoJava
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Source-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)Document is locked during a transactionACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyesyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes infousing specific database classes
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access controlnoUsers and roles with access to stored procedures
More information provided by the system vendor
DatabricksHBaseSequoiadbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetVoltDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksHBaseSequoiadbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetVoltDB
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