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DBMS > Apache Druid vs. Google BigQuery vs. Hazelcast vs. Linter vs. PostgreSQL

System Properties Comparison Apache Druid vs. Google BigQuery vs. Hazelcast vs. Linter vs. PostgreSQL

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonHazelcast  Xexclude from comparisonLinter  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataLarge scale data warehouse service with append-only tablesA widely adopted in-memory data gridRDBMS for high security requirementsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSKey-value storeRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMSDocument 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
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websitedruid.apache.orgcloud.google.com/­bigqueryhazelcast.comlinter.ruwww.postgresql.org
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­bigquery/­docshazelcast.org/­imdg/­docswww.postgresql.org/­docs
DeveloperApache Software Foundation and contributorsGoogleHazelcastrelex.ruPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release20122010200819901989 info1989: Postgres, 1996: PostgreSQL
Current release29.0.1, April 20245.3.6, November 202316.3, May 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++C
Server operating systemsLinux
OS X
Unix
hostedAll OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyes infoschema-less columns are supportedyesschema-freeyesyes
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.nonoyes infothe object must implement a serialization strategynoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL for queryingyesSQL-like query languageyesyes infostandard with numerous extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP/JSON APIJCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnouser defined functions infoin JavaScriptyes infoEvent Listeners, Executor Servicesyes infoproprietary syntax with the possibility to convert from PL/SQLuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnonoyes infoEventsyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShardingnonepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoReplicated MapSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoSince BigQuery is designed for querying dataone or two-phase-commit; repeatable reads; read commitedACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonoyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Role-based access controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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