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DBMS > Databricks vs. Dolt vs. VoltDB

System Properties Comparison Databricks vs. Dolt vs. VoltDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDolt  Xexclude from comparisonVoltDB  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.A MySQL compatible DBMS with Git-like versioning of data and schemaDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score102.66
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Score0.60
Rank#232  Overall
#106  Relational DBMS
Score1.21
Rank#164  Overall
#74  Relational DBMS
Websitewww.databricks.comgithub.com/­dolthub/­dolt
www.dolthub.com
www.voltdb.com
Technical documentationdocs.databricks.comdocs.dolthub.comdocs.voltdb.com
DeveloperDatabricksDoltHub IncVoltDB Inc.
Initial release201320182010
Current release11.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
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 languageGoJava, C++
Server operating systemshostedLinux
macOS
Windows
Linux
OS X infofor development
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
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesyes infoonly a subset of SQL 99
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
CLI Client
HTTP REST
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infocurrently in alpha releaseJava
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.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 Consistency
Foreign keys infoReferential integrityyesno infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlOnly one user is configurable, and must be specified in the config file at startupUsers and roles with access to stored procedures

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DatabricksDoltVoltDB
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