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DBMS > Apache IoTDB vs. HugeGraph vs. Ignite vs. IRONdb

System Properties Comparison Apache IoTDB vs. HugeGraph vs. Ignite vs. IRONdb

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonIgnite  Xexclude from comparisonIRONdb  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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 fast-speed and highly-scalable Graph DBMSApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelTime Series DBMSGraph DBMSKey-value store
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score0.15
Rank#339  Overall
#33  Graph DBMS
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Websiteiotdb.apache.orggithub.com/­hugegraph
hugegraph.apache.org
ignite.apache.orgwww.circonus.com/solutions/time-series-database/
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhugegraph.apache.org/­docsapacheignite.readme.io/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperApache Software FoundationBaiduApache Software FoundationCirconus LLC.
Initial release2018201820152017
Current release1.1.0, April 20230.9Apache Ignite 2.6V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++, Java, .NetC and C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
macOS
Unix
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infotext, numeric, histograms
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 infoalso supports composite index and range indexyesno
SQL infoSupport of SQLSQL-like query languagenoANSI-99 for query and DML statements, subset of DDLSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP API
TinkerPop Gremlin
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Groovy
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresyesasynchronous Gremlin script jobsyes (compute grid and cache interceptors can be used instead)yes, in Lua
Triggersyesnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)yes infodepending on used storage backend, e.g. Cassandra and HBaseShardingAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infodepending on used storage backend, e.g. Cassandra and HBaseyes (replicated cache)configurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkvia hugegraph-sparkyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynoyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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.yesyesyesno
User concepts infoAccess controlyesUsers, roles and permissionsSecurity Hooks for custom implementationsno

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More resources
Apache IoTDBHugeGraphIgniteIRONdb
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