DB-EnginesextremeDB - Data management wherever you need itEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

DBMS > Databricks vs. EsgynDB vs. Microsoft Azure Table Storage

System Properties Comparison Databricks vs. EsgynDB vs. Microsoft Azure Table Storage

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonMicrosoft Azure Table Storage  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.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelDocument store
Relational DBMS
Relational DBMSWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score99.29
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score2.63
Rank#94  Overall
#7  Wide column stores
Websitewww.databricks.comwww.esgyn.cnazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.databricks.com
DeveloperDatabricksEsgynMicrosoft
Initial release201320152012
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Java
Server operating systemshostedLinuxhosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyes
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.yesnono
Secondary indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesJava Stored Proceduresno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signatures

More information provided by the system vendor

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
DatabricksEsgynDBMicrosoft Azure Table Storage
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

Databricks buys feature engineering startup Fennel to enhance AI model development
18 April 2025, SiliconANGLE

Upskill your team on Azure Databricks with an on-demand webinar and Microsoft Learn
17 April 2025, Microsoft Azure

New! Use the ArcGIS API for Python in Databricks Notebooks
17 April 2025, Esri

BigQuery is 5x bigger than Snowflake and Databricks: What Google is doing to make it even better
17 April 2025, venturebeat.com

Palantir and Databricks Announce Strategic Product Partnership to Deliver Secure and Efficient AI to Customers
13 March 2025, PR Newswire

provided by Google News

How to use Azure Table storage in .Net
10 July 2024, InfoWorld

Working with Azure to Use and Manage Data Lakes
23 July 2024, Simplilearn.com

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, HackerNoon

Inside Azure File Storage
7 October 2015, Microsoft Azure

A Quick Overview of Microsoft Azure
1 June 2024, DataDrivenInvestor

provided by Google News



Share this page

Featured Products

Milvus logo

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

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

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

SingleStore logo

The data platform to build your intelligent applications.
Try it 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

Present your product here