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DBMS > Apache Druid vs. Datomic vs. Faircom EDGE vs. GridGain

System Properties Comparison Apache Druid vs. Datomic vs. Faircom EDGE vs. GridGain

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatomic  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonGridGain  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsGridGain is an in-memory computing platform, built on Apache Ignite
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSKey-value store
Relational DBMS
Key-value store
Relational 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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Websitedruid.apache.orgwww.datomic.comwww.faircom.com/­products/­faircom-edgewww.gridgain.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlwww.gridgain.com/­docs/­index.html
DeveloperApache Software Foundation and contributorsCognitectFairCom CorporationGridGain Systems, Inc.
Initial release2012201219792007
Current release29.0.1, April 20241.0.6735, June 2023V3, October 2020GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infolimited edition freecommercial infoRestricted, free version availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureANSI C, C++Java, C++, .Net
Server operating systemsLinux
OS X
Unix
All OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesyes
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.nonoyesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingnoyes infoANSI SQL queriesANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Clojure
Java
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyes info.Net, JavaScript, C/C++yes (compute grid and cache interceptors can be used instead)
TriggersnoBy using transaction functionsyesyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednone infoBut extensive use of caching in the application peersFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnone infoBut extensive use of caching in the application peersyes infoSynchronous and asynchronous realtime replication based on transaction logsyes (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 ConsistencyImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Security Hooks for custom implementations

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More resources
Apache DruidDatomicFaircom EDGE infoformerly c-treeEDGEGridGain
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