DB-EnginesEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

DBMS > Databricks vs. Tigris vs. TimescaleDB

System Properties Comparison Databricks vs. Tigris vs. TimescaleDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonTigris  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.A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructureA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Search engine
Time Series DBMS
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score83.29
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.04
Rank#360  Overall
#49  Document stores
#53  Key-value stores
#23  Search engines
#38  Time Series DBMS
Score3.90
Rank#74  Overall
#5  Time Series DBMS
Websitewww.databricks.comwww.tigrisdata.comwww.timescale.com
Technical documentationdocs.databricks.comwww.tigrisdata.com/­docsdocs.timescale.com
DeveloperDatabricksTigris Data, Inc.Timescale
Initial release201320222017
Current release2.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC
Server operating systemshostedLinux
macOS
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesnumerics, 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 indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
CLI Client
gRPC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
Go
Java
JavaScript (Node.js)
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes, using FoundationDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksTigrisTimescaleDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
DatabricksTigrisTimescaleDB
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the news

Ask the experts – Avassa and Databricks on closed-loop ML
12 July 2024, Edge Industry Review

Analytics and Data Science News for the Week of July 12; Updates from Anaconda, Databricks, Hebbia & More
12 July 2024, Solutions Review

Decoding the chess moves of Snowflake and Databricks
22 June 2024, SiliconANGLE News

Databricks launches LakeFlow to help its customers build their data pipelines
12 June 2024, TechCrunch

Databricks is one of the most valuable pre-IPO tech companies: Roth
20 June 2024, Investing.com

provided by Google News

Tigris Data Unveils Beta Launch of New Vector Search Tool
19 May 2023, Datanami

Tigris Data Launches All-in-One Developer Data Platform
27 September 2022, Datanami

FerretDB Provides Alternative to MongoDB
19 May 2023, Datanami

Latest Asigra platform targets SaaS backup for MSPs
6 March 2023, TechTarget

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, Microsoft

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



Share this page

Featured Products

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here