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DBMS > Apache Druid vs. Firebolt vs. Hyprcubd vs. PostgreSQL vs. Spark SQL

System Properties Comparison Apache Druid vs. Firebolt vs. Hyprcubd vs. PostgreSQL vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFirebolt  Xexclude from comparisonHyprcubd  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseServerless Time Series DBMSWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score1.73
Rank#140  Overall
#63  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orgwww.firebolt.iohyprcubd.com (offline)www.postgresql.orgspark.apache.org/­sql
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.firebolt.iowww.postgresql.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsFirebolt Analytics Inc.Hyprcubd, Inc.PostgreSQL Global Development Group infowww.postgresql.org/­developerApache Software Foundation
Initial release201220201989 info1989: Postgres, 1996: PostgreSQL2014
Current release29.0.1, April 202416.3, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialOpen Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
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Implementation languageJavaGoCScala
Server operating systemsLinux
OS X
Unix
hostedhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infotime, int, uint, float, stringyesyes
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.nonoyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLSQL for queryingyesSQL-like query languageyes infostandard with numerous extensionsSQL-like DML and DDL statements
APIs and other access methodsJDBC
RESTful HTTP/JSON API
.Net
ODBC
RESTful HTTP API
gRPC (https)ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedpartitioning by range, list and (since PostgreSQL 11) by hashyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesdepending on storage layerSource-replica replication infoother methods possible by using 3rd party extensionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesnoyesyes
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.nononono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemtoken accessfine grained access rights according to SQL-standardno

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More resources
Apache DruidFireboltHyprcubdPostgreSQLSpark SQL
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