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DBMS > Databricks vs. Quasardb vs. RavenDB vs. Valentina Server

System Properties Comparison Databricks vs. Quasardb vs. RavenDB vs. Valentina Server

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonQuasardb  Xexclude from comparisonRavenDB  Xexclude from comparisonValentina Server  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.Distributed, high-performance timeseries databaseOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseObject-relational database and reports server
Primary database modelDocument store
Relational DBMS
Time Series DBMSDocument storeRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time 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
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitewww.databricks.comquasar.airavendb.netwww.valentina-db.net
Technical documentationdocs.databricks.comdoc.quasar.ai/­masterravendb.net/­docsvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperDatabricksquasardbHibernating RhinosParadigma Software
Initial release2013200920101999
Current release3.14.1, January 20245.4, July 20225.7.5
License infoCommercial or Open Sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoAGPL version 3, commercial license availablecommercial
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++C#
Server operating systemshostedBSD
Linux
OS X
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes infointeger and binarynoyes
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 indexesyesyes infowith tagsyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query languageSQL-like query language (RQL)yes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
ODBC
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyesyes
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication with selectable replication factorMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodswith Hadoop integrationyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeyes
User concepts infoAccess controlCryptographically strong user authentication and audit trailAuthorization levels configured per client per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksQuasardbRavenDBValentina Server
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksQuasardbRavenDBValentina Server
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