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DBMS > Databricks vs. eXtremeDB vs. FoundationDB vs. Microsoft Azure AI Search

System Properties Comparison Databricks vs. eXtremeDB vs. FoundationDB vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisoneXtremeDB  Xexclude from comparisonFoundationDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in 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.Natively in-memory DBMS with options for persistency, high-availability and clusteringOrdered key-value store. Core features are complimented by layers.Search-as-a-service for web and mobile app development
Primary database modelDocument store
Relational DBMS
Relational DBMS
Time Series DBMS
Document store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Search engine
Secondary database modelsVector 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
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Websitewww.databricks.comwww.mcobject.comgithub.com/­apple/­foundationdbazure.microsoft.com/­en-us/­services/­search
Technical documentationdocs.databricks.comwww.mcobject.com/­docs/­extremedb.htmapple.github.io/­foundationdblearn.microsoft.com/­en-us/­azure/­search
DeveloperDatabricksMcObjectFoundationDBMicrosoft
Initial release2013200120132015
Current release8.2, 20216.2.28, November 2020V1
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++
Server operating systemshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free infosome layers support schemasyes
Typing infopredefined data types such as float or dateyesno infosome layers support typingyes
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 infosupport of XML interfaces availableno
Secondary indexesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLyes infowith the option: eXtremeSQLsupported in specific SQL layer onlyno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesin SQL-layer onlyno
Triggersyes infoby defining eventsnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yesyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyLinearizable consistencyImmediate Consistency
Foreign keys infoReferential integrityyesin SQL-layer onlyno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnoyes infousing Azure authentication
More information provided by the system vendor
DatabrickseXtremeDBFoundationDBMicrosoft Azure AI Search
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more

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DatabrickseXtremeDBFoundationDBMicrosoft Azure AI Search
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