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DBMS > Databricks vs. Kinetica vs. RavenDB vs. YugabyteDB

System Properties Comparison Databricks vs. Kinetica vs. RavenDB vs. YugabyteDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonKinetica  Xexclude from comparisonRavenDB  Xexclude from comparisonYugabyteDB  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.Fully vectorized database across both GPUs and CPUsOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Graph DBMS
Spatial DBMS
Time Series DBMS
Document store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Score2.63
Rank#109  Overall
#53  Relational DBMS
Websitewww.databricks.comwww.kinetica.comravendb.netwww.yugabyte.com
Technical documentationdocs.databricks.comdocs.kinetica.comravendb.net/­docsdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperDatabricksKineticaHibernating RhinosYugabyte Inc.
Initial release2013201220102017
Current release7.1, August 20215.4, July 20222.19, September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 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.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageC, C++C#C and C++
Server operating systemshostedLinuxLinux
macOS
Raspberry Pi
Windows
Linux
OS X
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freedepending on used data model
Typing infopredefined data types such as float or dateyesnoyes
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.yesnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like DML and DDL statementsSQL-like query language (RQL)yes, PostgreSQL compatible
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful 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
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesPython
R
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsyesyes infosql, plpgsql, C
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replicationBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationDefault 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.Strong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, Cluster-wide transaction availableDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and roles on table levelAuthorization levels configured per client per databaseyes
More information provided by the system vendor
DatabricksKineticaRavenDBYugabyteDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesPostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosSystems of record and engagement for cloud native applications that require resilience,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsApache 2.0 license for the database
» more

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