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DBMS > Apache Druid vs. ArangoDB vs. GridGain vs. HugeGraph

System Properties Comparison Apache Druid vs. ArangoDB vs. GridGain vs. HugeGraph

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonArangoDB  Xexclude from comparisonGridGain  Xexclude from comparisonHugeGraph  Xexclude from comparison
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 IgniteA fast-speed and highly-scalable Graph DBMS
Primary database modelRelational DBMS
Time Series DBMS
Document store
Graph DBMS
Key-value store
Search engine
Key-value store
Relational DBMS
Graph 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
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websitedruid.apache.orgarangodb.comwww.gridgain.comgithub.com/­hugegraph
hugegraph.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.arangodb.comwww.gridgain.com/­docs/­index.htmlhugegraph.apache.org/­docs
Social network pagesLinkedInTwitterYouTubeFacebookInstagram
DeveloperApache Software Foundation and contributorsArangoDB Inc.GridGain Systems, Inc.Baidu
Initial release2012201220072018
Current release29.0.1, April 20243.11.5, November 2023GridGain 8.5.10.9
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; Commercial license (Enterprise) availablecommercialOpen Source infoApache Version 2.0
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++, .NetJava
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Unix
Data schemeyes infoschema-less columns are supportedschema-free infoautomatically recognizes schema within a collectionyesyes
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.noyesno
Secondary indexesyesyesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLSQL for queryingnoANSI-99 for query and DML statements, subset of DDLno
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
Java API
RESTful HTTP API
TinkerPop Gremlin
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
Groovy
Java
Python
Server-side scripts infoStored proceduresnoJavaScriptyes (compute grid and cache interceptors can be used instead)asynchronous Gremlin script jobs
Triggersnonoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infosince version 2.0Shardingyes infodepending on used storage backend, e.g. Cassandra and HBase
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 infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infocan be done with stored procedures in JavaScriptyes (compute grid and hadoop accelerator)via hugegraph-spark
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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes inforelationships in graphsnoyes infoedges in graph
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.noyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesSecurity Hooks for custom implementationsUsers, roles and permissions
More information provided by the system vendor
Apache DruidArangoDBGridGainHugeGraph
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 DruidArangoDBGridGainHugeGraph
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