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DBMS > Databricks vs. HBase vs. Sequoiadb vs. TimescaleDB

System Properties Comparison Databricks vs. HBase vs. Sequoiadb vs. TimescaleDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonSequoiadb  Xexclude from comparisonTimescaleDB  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 time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Relational DBMS
Wide column storeDocument store
Relational DBMS
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.34
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score31.60
Rank#26  Overall
#2  Wide column stores
Score0.50
Rank#264  Overall
#42  Document stores
#121  Relational DBMS
Score5.33
Rank#72  Overall
#4  Time Series DBMS
Websitewww.databricks.comhbase.apache.orgwww.sequoiadb.comwww.timescale.com
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=indexdocs.timescale.com
DeveloperDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetSequoiadb Ltd.Timescale
Initial release2013200820132017
Current release2.3.4, January 20212.13.0, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
LinuxLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyes infooid, date, timestamp, binary, regexnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.yesnonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSONADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C++
Java
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoCoprocessors in JavaJavaScriptuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Source-replica replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
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
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access controlfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksHBaseSequoiadbTimescaleDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksHBaseSequoiadbTimescaleDB
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