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DBMS > Apache Druid vs. Faircom DB vs. GeoSpock vs. GridGain

System Properties Comparison Apache Druid vs. Faircom DB vs. GeoSpock vs. GridGain

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGeoSpock  Xexclude from comparisonGridGain  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Spatial and temporal data processing engine for extreme data scaleGridGain is an in-memory computing platform, built on Apache Ignite
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Relational DBMSKey-value store
Relational DBMS
Secondary database modelsTime Series 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
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Websitedruid.apache.orgwww.faircom.com/­products/­faircom-dbgeospock.comwww.gridgain.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.gridgain.com/­docs/­index.html
DeveloperApache Software Foundation and contributorsFairCom CorporationGeoSpockGridGain Systems, Inc.
Initial release201219792007
Current release29.0.1, April 2024V12, November 20202.0, September 2019GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infoRestricted, free version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++Java, JavascriptJava, C++, .Net
Server operating systemsLinux
OS X
Unix
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedLinux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedschema free, schema optional, schema required, partial schema,yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes
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.nononoyes
Secondary indexesyesyestemporal, categoricalyes
SQL infoSupport of SQLSQL for queryingyes, ANSI SQL with proprietary extensionsANSI SQL for query only (using Presto)ANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBCHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++noyes (compute grid and cache interceptors can be used instead)
Triggersnoyesnoyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually ConsistentnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
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-standard with additional protections for filesAccess rights for users can be defined per tableSecurity Hooks for custom implementations

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More resources
Apache DruidFaircom DB infoformerly c-treeACEGeoSpockGridGain
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