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DBMS > Apache Druid vs. Fujitsu Enterprise Postgres vs. GBase vs. Google Cloud Spanner vs. Heroic

System Properties Comparison Apache Druid vs. Fujitsu Enterprise Postgres vs. GBase vs. Google Cloud Spanner vs. Heroic

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGBase  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHeroic  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.Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
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
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Websitedruid.apache.orgwww.postgresql.fastware.comwww.gbase.cncloud.google.com/­spannergithub.com/­spotify/­heroic
Technical documentationdruid.apache.org/­docs/­latest/­designwww.postgresql.fastware.com/­product-manualscloud.google.com/­spanner/­docsspotify.github.io/­heroic
DeveloperApache Software Foundation and contributorsPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGeneral Data Technology Co., Ltd.GoogleSpotify
Initial release2012200420172014
Current release29.0.1, April 2024Fujitsu Enterprise Postgres 14, January 2022GBase 8a, GBase 8s, GBase 8c
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC, Java, PythonJava
Server operating systemsLinux
OS X
Unix
Linux
Windows
Linuxhosted
Data schemeyes infoschema-less columns are supportedyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesyesyesyesyesyes infovia Elasticsearch
SQL infoSupport of SQLSQL for queryingyesStandard with numerous extensionsyes infoQuery statements complying to ANSI 2011no
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
C API
JDBC
ODBC
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functionsuser defined functionsnono
Triggersnoyesyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedpartitioning by range, list and by hashhorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationyesMulti-source replication with 3 replicas for regional instances.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID infoStrict serializable isolationno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
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-standardyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache DruidFujitsu Enterprise PostgresGBaseGoogle Cloud SpannerHeroic
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