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DBMS > Databricks vs. EventStoreDB vs. eXtremeDB vs. Vitess

System Properties Comparison Databricks vs. EventStoreDB vs. eXtremeDB vs. Vitess

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEventStoreDB  Xexclude from comparisoneXtremeDB  Xexclude from comparisonVitess  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.Industrial-strength, open-source database solution built from the ground up for event sourcing.Natively in-memory DBMS with options for persistency, high-availability and clusteringScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument store
Relational DBMS
Event StoreRelational DBMS
Time Series DBMS
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.10
Rank#179  Overall
#1  Event Stores
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.databricks.comwww.eventstore.comwww.mcobject.comvitess.io
Technical documentationdocs.databricks.comdevelopers.eventstore.comwww.mcobject.com/­docs/­extremedb.htmvitess.io/­docs
DeveloperDatabricksEvent Store LimitedMcObjectThe Linux Foundation, PlanetScale
Initial release2013201220012013
Current release21.2, February 20218.2, 202115.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++Go
Server operating systemshostedLinux
Windows
AIX
HP-UX
Linux
macOS
Solaris
Windows
Docker
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
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.yesno infosupport of XML interfaces available
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infowith the option: eXtremeSQLyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyes infoproprietary syntax
Triggersyes infoby defining eventsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyes infotable locks or row locks depending on storage engine
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.noyesyes
User concepts infoAccess controlUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
DatabricksEventStoreDBeXtremeDBVitess
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...
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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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More resources
DatabricksEventStoreDBeXtremeDBVitess
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