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

DBMS > Apache Phoenix vs. Databricks vs. FatDB vs. Microsoft Azure Table Storage vs. Yaacomo

System Properties Comparison Apache Phoenix vs. Databricks vs. FatDB vs. Microsoft Azure Table Storage vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonYaacomo  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseThe 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 .NET NoSQL DBMS that can integrate with and extend SQL Server.A Wide Column Store for rapid development using massive semi-structured datasetsOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSDocument store
Relational DBMS
Document store
Key-value store
Wide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score3.55
Rank#80  Overall
#6  Wide column stores
Websitephoenix.apache.orgwww.databricks.comazure.microsoft.com/­en-us/­services/­storage/­tablesyaacomo.com
Technical documentationphoenix.apache.orgdocs.databricks.com
DeveloperApache Software FoundationDatabricksFatCloudMicrosoftQ2WEB GmbH
Initial release20142013201220122009
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#
Server operating systemsLinux
Unix
Windows
hostedWindowshostedAndroid
Linux
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyesnono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyeswith Databricks SQLno infoVia inetgration in SQL Servernoyes
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
RESTful HTTP APIJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Python
R
Scala
C#.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsuser defined functions and aggregatesyes infovia applicationsno
Triggersnoyes infovia applicationsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesselectable replication factoryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnooptimistic lockingACID
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.yesnonoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyno infoCan implement custom security layer via applicationsAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache PhoenixDatabricksFatDBMicrosoft Azure Table StorageYaacomo
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
Apache PhoenixDatabricksFatDBMicrosoft Azure Table StorageYaacomo
DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021,  Krishna Maheshwari (sponsor) 

show all

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

show all

Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix
2 June 2016, AWS Blog

Deep dive into Azure HDInsight 4.0
25 September 2018, azure.microsoft.com

Hortonworks Starts Hadoop Summit with Data Platform Update
28 June 2016, ADT Magazine

Apache Drill Adds New Data Formats
28 March 2022, iProgrammer

Amazon EMR 4.7.0 – Apache Tez & Phoenix, Updates to Existing Apps
2 June 2016, AWS Blog

provided by Google News

Saudi Arabia’s Sovereign Wealth Fund’s Big AI Bets Include Mistral And Databricks
24 September 2024, Forbes

Databricks could launch IPO in two months but biding time despite investor pressure, CEO says
13 September 2024, ION Analytics

Databricks reportedly paid $2 billion in Tabular acquisition
14 August 2024, TechCrunch

Inside the Snowflake — Databricks Rivalry, and Why Both Fear Microsoft
14 August 2024, Bloomberg

The People in Charge at Databricks as It Moves Toward a Potential IPO
24 July 2024, The Information

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

Azure Cosmos DB Data Migration tool imports from Azure Table storage
5 May 2015, azure.microsoft.com

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

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

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

RaimaDB logo

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

SingleStore logo

The data platform to build your intelligent applications.
Try it free.

Milvus logo

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

Present your product here