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DBMS > Citus vs. Heroic vs. Spark SQL vs. YugabyteDB

System Properties Comparison Citus vs. Heroic vs. Spark SQL vs. YugabyteDB

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonHeroic  Xexclude from comparisonSpark SQL  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchSpark 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 DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.91
Rank#102  Overall
#51  Relational DBMS
Websitewww.citusdata.comgithub.com/­spotify/­heroicspark.apache.org/­sqlwww.yugabyte.com
Technical documentationdocs.citusdata.comspotify.github.io/­heroicspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperSpotifyApache Software FoundationYugabyte Inc.
Initial release2010201420142017
Current release8.1, December 20183.5.0 ( 2.13), September 20232.19, September 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
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 languageCJavaScalaC and C++
Server operating systemsLinuxLinux
OS X
Windows
Linux
OS X
Data schemeyesschema-freeyesdepending 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.yes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesyesyes infovia Elasticsearchnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoSQL-like DML and DDL statementsyes, PostgreSQL compatible
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HQL (Heroic Query Language, a JSON-based language)
HTTP API
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 languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nonoyes infosql, plpgsql, C
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesnoneBased 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 ConsistencyEventual Consistency
Immediate Consistency
Strong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoDistributed 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.nononono
User concepts infoAccess controlfine grained access rights according to SQL-standardnoyes
More information provided by the system vendor
CitusHeroicSpark 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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CitusHeroicSpark SQLYugabyteDB
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