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DBMS > Apache IoTDB vs. Elasticsearch vs. GridGain vs. HugeGraph

System Properties Comparison Apache IoTDB vs. Elasticsearch vs. GridGain vs. HugeGraph

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonGridGain  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricGridGain is an in-memory computing platform, built on Apache IgniteA fast-speed and highly-scalable Graph DBMS
Primary database modelTime Series DBMSSearch engineKey-value store
Relational DBMS
Graph DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websiteiotdb.apache.orgwww.elastic.co/­elasticsearchwww.gridgain.comgithub.com/­hugegraph
hugegraph.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlwww.gridgain.com/­docs/­index.htmlhugegraph.apache.org/­docs
DeveloperApache Software FoundationElasticGridGain Systems, Inc.Baidu
Initial release2018201020072018
Current release1.1.0, April 20238.6, January 2023GridGain 8.5.10.9
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoElastic LicensecommercialOpen 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 languageJavaJavaJava, C++, .NetJava
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinux
OS X
Solaris
Windows
Linux
macOS
Unix
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes
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.nonoyesno
Secondary indexesyesyes infoAll search fields are automatically indexedyesyes infoalso supports composite index and range index
SQL infoSupport of SQLSQL-like query languageSQL-like query languageANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Groovy
Java
Python
Server-side scripts infoStored proceduresyesyesyes (compute grid and cache interceptors can be used instead)asynchronous Gremlin script jobs
Triggersyesyes infoby using the 'percolation' featureyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesyes (replicated cache)yes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkES-Hadoop Connectoryes (compute grid and hadoop accelerator)via hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
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.yesMemcached and Redis integrationyesyes
User concepts infoAccess controlyesSecurity Hooks for custom implementationsUsers, roles and permissions

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More resources
Apache IoTDBElasticsearchGridGainHugeGraph
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