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DBMS > Drizzle vs. Heroic vs. Sequoiadb vs. Spark SQL

System Properties Comparison Drizzle vs. Heroic vs. Sequoiadb vs. Spark SQL

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHeroic  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSDocument store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­spotify/­heroicwww.sequoiadb.comspark.apache.org/­sql
Technical documentationspotify.github.io/­heroicwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDrizzle project, originally started by Brian AkerSpotifySequoiadb Ltd.Apache Software Foundation
Initial release2008201420132014
Current release7.2.4, September 20123.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache 2.0Open Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++Scala
Server operating systemsFreeBSD
Linux
OS X
LinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infooid, date, timestamp, binary, regexyes
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.nonono
Secondary indexesyesyes infovia Elasticsearchyesno
SQL infoSupport of SQLyes infowith proprietary extensionsnoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBCHQL (Heroic Query Language, a JSON-based language)
HTTP API
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesC
C++
Java
PHP
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoJavaScriptno
Triggersno infohooks for callbacks inside the server can be used.nonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoDocument is locked during a transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPsimple password-based access controlno

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More resources
DrizzleHeroicSequoiadbSpark SQL
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