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DBMS > Databricks vs. HBase vs. Sequoiadb vs. Tkrzw vs. Warp 10

System Properties Comparison Databricks vs. HBase vs. Sequoiadb vs. Tkrzw vs. Warp 10

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 comparisonWarp 10  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 CabinetTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelDocument store
Relational DBMS
Wide column storeDocument store
Relational DBMS
Key-value storeTime Series 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
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitewww.databricks.comhbase.apache.orgwww.sequoiadb.comdbmx.net/­tkrzwwww.warp10.io
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=indexwww.warp10.io/­content/­02_Getting_started
DeveloperDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetSequoiadb Ltd.Mikio HirabayashiSenX
Initial release20132008201320202015
Current release2.3.4, January 20210.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoServer: AGPL; Client: Apache V2Open Source infoApache Version 2.0Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++Java
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
LinuxLinux
macOS
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleschema-freeschema-freeschema-free
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.yesnononono
Secondary indexesyesnoyesno
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query languagenono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSONHTTP API
Jupyter
WebSocket
Supported programming languagesPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C++
Java
PHP
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoCoprocessors in JavaJavaScriptnoyes infoWarpScript
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Source-replica replicationnoneselectable replication factor infobased on HBase
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 ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)Document is locked during a transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes infousing specific database classesyes
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access controlnoMandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
DatabricksHBaseSequoiadbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetWarp 10
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHBaseSequoiadbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetWarp 10
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