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DBMS > Apache Druid vs. ArangoDB vs. GridGain vs. Teradata Aster

System Properties Comparison Apache Druid vs. ArangoDB vs. GridGain vs. Teradata Aster

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonArangoDB  Xexclude from comparisonGridGain  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataNative multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.GridGain is an in-memory computing platform, built on Apache IgnitePlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMS
Time Series DBMS
Document store
Graph DBMS
Key-value store
Search engine
Key-value store
Relational DBMS
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
Score3.32
Rank#90  Overall
#15  Document stores
#5  Graph DBMS
#12  Key-value stores
#10  Search engines
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Websitedruid.apache.orgarangodb.comwww.gridgain.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.arangodb.comwww.gridgain.com/­docs/­index.html
Social network pagesLinkedInTwitterYouTubeFacebookInstagram
DeveloperApache Software Foundation and contributorsArangoDB Inc.GridGain Systems, Inc.Teradata
Initial release2012201220072005
Current release29.0.1, April 20243.11.5, November 2023GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; Commercial license (Enterprise) availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java, C++, .Net
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyes infoschema-less columns are supportedschema-free infoautomatically recognizes schema within a collectionyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyes infostring, double, boolean, list, hashyesyes
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.noyesyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingnoANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoJavaScriptyes (compute grid and cache interceptors can be used instead)R packages
Triggersnonoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infosince version 2.0ShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replication with configurable replication factoryes (replicated cache)yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infocan be done with stored procedures in JavaScriptyes (compute grid and hadoop accelerator)yes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoconfigurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes inforelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
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.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DruidArangoDBGridGainTeradata Aster
Specific characteristicsGraph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more
Competitive advantagesConsolidation: As a native multi-model database, can be used as a full blown document...
» more
Typical application scenariosNative multi-model in ArangoDB is being used for a broad range of projects across...
» more
Key customersCisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more
Market metricsArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more
Licensing and pricing modelsVery permissive Apache 2 License for Community Edition & commercial licenses are...
» more

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More resources
Apache DruidArangoDBGridGainTeradata Aster
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The Weight of Relational Databases: Time for Multi-Model?
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