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DBMS > Apache Druid vs. Google BigQuery vs. Greenplum vs. GridGain

System Properties Comparison Apache Druid vs. Google BigQuery vs. Greenplum vs. GridGain

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonGreenplum  Xexclude from comparisonGridGain  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 tablesAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.GridGain is an in-memory computing platform, built on Apache Ignite
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSKey-value store
Relational DBMS
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
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Websitedruid.apache.orgcloud.google.com/­bigquerygreenplum.orgwww.gridgain.com
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­bigquery/­docsdocs.greenplum.orgwww.gridgain.com/­docs/­index.html
DeveloperApache Software Foundation and contributorsGooglePivotal Software Inc.GridGain Systems, Inc.
Initial release2012201020052007
Current release29.0.1, April 20247.0.0, September 2023GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .Net
Server operating systemsLinux
OS X
Unix
hostedLinuxLinux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesyesyes
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.nonoyes infosince Version 4.2yes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL for queryingyesyesANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP/JSON APIJDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
Java
Perl
Python
R
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnouser defined functions infoin JavaScriptyesyes (compute grid and cache interceptors can be used instead)
Triggersnonoyesyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoSince BigQuery is designed for querying dataACIDACID
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.nononoyes
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)fine grained access rights according to SQL-standardSecurity Hooks for custom implementations

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More resources
Apache DruidGoogle BigQueryGreenplumGridGain
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