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DBMS > Apache Druid vs. Fujitsu Enterprise Postgres vs. Heroic vs. Stardog

System Properties Comparison Apache Druid vs. Fujitsu Enterprise Postgres vs. Heroic vs. Stardog

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonHeroic  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMSGraph DBMS
RDF store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitedruid.apache.orgwww.postgresql.fastware.comgithub.com/­spotify/­heroicwww.stardog.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.postgresql.fastware.com/­product-manualsspotify.github.io/­heroicdocs.stardog.com
DeveloperApache Software Foundation and contributorsPostgreSQL Global Development Group, Fujitsu Australia Software TechnologySpotifyStardog-Union
Initial release201220142010
Current release29.0.1, April 2024Fujitsu Enterprise Postgres 14, January 20227.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJavaJava
Server operating systemsLinux
OS X
Unix
Linux
Windows
Linux
macOS
Windows
Data schemeyes infoschema-less columns are supportedyesschema-freeschema-free and OWL/RDFS-schema support
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.nonono infoImport/export of XML data possible
Secondary indexesyesyesyes infovia Elasticsearchyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL for queryingyesnoYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HQL (Heroic Query Language, a JSON-based language)
HTTP API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functionsnouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedpartitioning by range, list and by hashShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationyesMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyesnoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAccess rights for users and roles
More information provided by the system vendor
Apache DruidFujitsu Enterprise PostgresHeroicStardog
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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Apache DruidFujitsu Enterprise PostgresHeroicStardog
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