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DBMS > Databricks vs. Drizzle vs. Splice Machine vs. VictoriaMetrics

System Properties Comparison Databricks vs. Drizzle vs. Splice Machine vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonSplice Machine  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines 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.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSTime Series 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
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitewww.databricks.comsplicemachine.comvictoriametrics.com
Technical documentationdocs.databricks.comsplicemachine.com/­how-it-worksdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperDatabricksDrizzle project, originally started by Brian AkerSplice MachineVictoriaMetrics
Initial release2013200820142018
Current release7.2.4, September 20123.1, March 2021v1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0
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++JavaGo
Server operating systemshostedFreeBSD
Linux
OS X
Linux
OS X
Solaris
Windows
FreeBSD
Linux
macOS
OpenBSD
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 SQLyes infowith proprietary extensionsyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCJDBC
Native Spark Datasource
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infoJavano
Triggersno infohooks for callbacks inside the server can be used.yesno
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Synchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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 controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DatabricksDrizzleSplice MachineVictoriaMetrics
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDrizzleSplice MachineVictoriaMetrics
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