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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBangdb  Xexclude from comparisonHugeGraph  Xexclude from comparisonIgnite  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 FlinkConverged and high performance database for device data, events, time series, document and graphA 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.
Primary database modelTime Series DBMSDocument store
Graph DBMS
Time Series DBMS
Graph DBMSKey-value store
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websiteiotdb.apache.orgbangdb.comgithub.com/­hugegraph
hugegraph.apache.org
ignite.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bangdb.comhugegraph.apache.org/­docsapacheignite.readme.io/­docs
DeveloperApache Software FoundationSachin Sinha, BangDBBaiduApache Software Foundation
Initial release2018201220182015
Current release1.1.0, April 2023BangDB 2.0, October 20210.9Apache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD 3Open Source infoApache Version 2.0Open Source infoApache 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, C++JavaC++, Java, .Net
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
macOS
Unix
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesyes
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.nononoyes
Secondary indexesyesyes infosecondary, composite, nested, reverse, geospatialyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLSQL-like query languageSQL like support with command line toolnoANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJDBC
Native API
Proprietary protocol
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
Python
Groovy
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesnoasynchronous Gremlin script jobsyes (compute grid and cache interceptors can be used instead)
Triggersyesyes, Notifications (with Streaming only)noyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor, Knob for CAP (enterprise version only)yes infodepending on used storage backend, e.g. Cassandra and HBaseyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknovia hugegraph-sparkyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Tunable consistency, set CAP knob accordinglyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, run db with in-memory only modeyesyes
User concepts infoAccess controlyesyes (enterprise version only)Users, roles and permissionsSecurity Hooks for custom implementations

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More resources
Apache IoTDBBangdbHugeGraphIgnite
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