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

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

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonLovefield  Xexclude from comparisonSequoiadb  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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 BigTableEmbeddable relational database for web apps written in pure JavaScriptNewSQL 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 Cabinet
Primary database modelDocument store
Relational DBMS
Wide column storeRelational DBMSDocument store
Relational DBMS
Key-value store
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
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.databricks.comhbase.apache.orggoogle.github.io/­lovefieldwww.sequoiadb.comdbmx.net/­tkrzw
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetGoogleSequoiadb Ltd.Mikio Hirabayashi
Initial release20132008201420132020
Current release2.3.4, January 20212.1.12, February 20170.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoServer: AGPL; Client: Apache V2Open Source infoApache Version 2.0
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 languageJavaJavaScriptC++C++
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinuxLinux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleyesschema-freeschema-free
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesyes infooid, date, timestamp, binary, regexno
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 indexesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query language infovia JavaScript builder patternSQL-like query languageno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSON
Supported programming languagesPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
JavaScript.Net
C++
Java
PHP
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoCoprocessors in JavanoJavaScriptno
TriggersyesUsing read-only observersnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
noneSource-replica replicationnone
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 integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACIDDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDBnoyes infousing specific database classes
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnosimple password-based access controlno
More information provided by the system vendor
DatabricksHBaseLovefieldSequoiadbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksHBaseLovefieldSequoiadbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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