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DBMS > Kinetica vs. Snowflake vs. Spark SQL vs. YugabyteDB

System Properties Comparison Kinetica vs. Snowflake vs. Spark SQL vs. YugabyteDB

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSnowflake  Xexclude from comparisonSpark SQL  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsCloud-based data warehousing service for structured and semi-structured dataSpark SQL is a component on top of 'Spark Core' for structured data processingHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#229  Overall
#105  Relational DBMS
Score125.38
Rank#9  Overall
#6  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score3.21
Rank#103  Overall
#53  Relational DBMS
Websitewww.kinetica.comwww.snowflake.comspark.apache.org/­sqlwww.yugabyte.com
Technical documentationdocs.kinetica.comdocs.snowflake.net/­manuals/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperKineticaSnowflake Computing Inc.Apache Software FoundationYugabyte Inc.
Initial release2012201420142017
Current release7.1, August 20213.5.0 ( 2.13), September 20232.19, September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
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++ScalaC and C++
Server operating systemsLinuxhostedLinux
OS X
Windows
Linux
OS X
Data schemeyesyes infosupport of semi-structured data formats (JSON, XML, Avro)yesdepending on used data model
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyesnono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like DML and DDL statementsyes, PostgreSQL compatible
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
CLI Client
JDBC
ODBC
JDBC
ODBC
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 languagesC++
Java
JavaScript (Node.js)
Python
JavaScript (Node.js)
Python
Java
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsnoyes infosql, plpgsql, C
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeno infosimilar concept for controling cloud resourcesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyesyes, utilizing Spark CoreHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnoneBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoDistributed 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.yes infoGPU vRAM or System RAMnonono
User concepts infoAccess controlAccess rights for users and roles on table levelUsers with fine-grained authorization concept, user roles and pluggable authenticationnoyes
More information provided by the system vendor
KineticaSnowflakeSpark SQLYugabyteDB
Specific characteristicsYugabyteDB 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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More resources
KineticaSnowflakeSpark SQLYugabyteDB
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