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DBMS > Databricks vs. Drizzle vs. FatDB vs. Fauna vs. TimescaleDB

System Properties Comparison Databricks vs. Drizzle vs. FatDB vs. Fauna vs. TimescaleDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonFatDB  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonTimescaleDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the 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.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument store
Key-value store
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Time Series DBMS
Secondary database modelsRelational 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
Score1.55
Rank#151  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitewww.databricks.comfauna.comwww.timescale.com
Technical documentationdocs.databricks.comdocs.fauna.comdocs.timescale.com
DeveloperDatabricksDrizzle project, originally started by Brian AkerFatCloudFauna, Inc.Timescale
Initial release20132008201220142017
Current release7.2.4, September 20122.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#ScalaC
Server operating systemshostedFreeBSD
Linux
OS X
WindowshostedLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnonumerics, 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.yesnoyes
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsno infoVia inetgration in SQL Servernoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
C#C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infovia applicationsuser defined functionsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersno infohooks for callbacks inside the server can be used.yes infovia applicationsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoconsistent hashingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
selectable replication factorMulti-source replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDACID
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.nonono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPno infoCan implement custom security layer via applicationsIdentity management, authentication, and access controlfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksDrizzleFatDBFauna infopreviously named FaunaDBTimescaleDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDrizzleFatDBFauna infopreviously named FaunaDBTimescaleDB
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