DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Databricks vs. Graphite vs. Valentina Server

System Properties Comparison Databricks vs. Graphite vs. Valentina Server

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGraphite  Xexclude from comparisonValentina Server  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.Data logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperObject-relational database and reports server
Primary database modelDocument store
Relational DBMS
Time Series 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
Score4.83
Rank#67  Overall
#4  Time Series DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websitewww.databricks.comgithub.com/­graphite-project/­graphite-webwww.valentina-db.net
Technical documentationdocs.databricks.comgraphite.readthedocs.iovalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperDatabricksChris DavisParadigma Software
Initial release201320061999
Current release5.7.5
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial
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 languagePython
Server operating systemshostedLinux
Unix
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateNumeric data onlyyes
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.yesno
Secondary indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP API
Sockets
ODBC
Supported programming languagesPython
R
Scala
JavaScript (Node.js)
Python
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencynone
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infolocking
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlnofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksGraphiteValentina Server
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
DatabricksGraphiteValentina Server
DB-Engines blog posts

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

show all

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Databricks is Taking the Ultimate Risk of Building 'USB for AI' – AIM
15 June 2024, Analytics India Magazine

The Three Big Announcements by Databricks AI Team in June 2024
17 June 2024, MarkTechPost

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

Databricks tells investors annualized revenue will reach $2.4 billion at midway point of year
13 June 2024, CNBC

Databricks open-sources Unity Catalog, challenging Snowflake on interoperability for data workloads
12 June 2024, VentureBeat

provided by Google News

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

The value of time series data and TSDBs
10 June 2021, InfoWorld

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

A Look at Valentina — SitePoint
18 April 2014, SitePoint

MySQL GUI Tools for Windows and Ubuntu/Linux: Top 8 free or open source
7 December 2018, H2S Media

provided by Google News



Share this page

Featured Products

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

Neo4j logo

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

Present your product here