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DBMS > Databricks vs. PostGIS vs. Sequoiadb vs. TimescaleDB vs. Yaacomo

System Properties Comparison Databricks vs. PostGIS vs. Sequoiadb vs. TimescaleDB vs. Yaacomo

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonPostGIS  Xexclude from comparisonSequoiadb  Xexclude from comparisonTimescaleDB  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
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.Spatial extension of PostgreSQLNewSQL database with distributed OLTP and SQLA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Relational DBMS
Spatial DBMSDocument store
Relational DBMS
Time Series DBMSRelational DBMS
Secondary database modelsRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score21.72
Rank#29  Overall
#1  Spatial DBMS
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitewww.databricks.compostgis.netwww.sequoiadb.comwww.timescale.comyaacomo.com
Technical documentationdocs.databricks.compostgis.net/­documentationwww.sequoiadb.com/­en/­index.php?m=Files&a=indexdocs.timescale.com
DeveloperDatabricksSequoiadb Ltd.TimescaleQ2WEB GmbH
Initial release20132005201320172009
Current release3.4.2, February 20242.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoGPL v2.0Open Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0commercial
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 languageCC++C
Server operating systemshostedLinuxLinux
OS X
Windows
Android
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infooid, date, timestamp, binary, regexnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.yesyesnoyesno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesSQL-like query languageyes infofull PostgreSQL SQL syntaxyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
proprietary protocol using JSONADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesPython
R
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 aggregatesuser defined functionsJavaScriptuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesyes infobased on PostgreSQLShardingyes, across time and space (hash partitioning) attributeshorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infobased on PostgreSQLSource-replica replicationSource-replica replication with hot standby and reads on replicas infoSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDDocument is locked during a transactionACIDACID
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.nonononoyes
User concepts infoAccess controlyes infobased on PostgreSQLsimple password-based access controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksPostGISSequoiadbTimescaleDBYaacomo
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksPostGISSequoiadbTimescaleDBYaacomo
DB-Engines blog posts

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Recent citations in the news

Exclusive | Databricks to Buy Data-Management Startup Tabular in Bid for AI Clients
4 June 2024, The Wall Street Journal

Databricks acquires data optimization startup Tabular in fresh challenge to Snowflake
4 June 2024, CNBC

Databricks' $1B Tabular buy raises questions around table format wars
5 June 2024, The Register

Databricks CEO Ali Ghodsi on Snowflake rivalry and the 'why' behind Databricks' latest billion-dollar deal
5 June 2024, Yahoo Finance

Databricks buys Tabular to win the Iceberg war – Blocks and Files
5 June 2024, Blocks and Files

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, azure.microsoft.com

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

provided by Google News



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