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DBMS > Apache IoTDB vs. ArangoDB vs. HugeGraph vs. Netezza

System Properties Comparison Apache IoTDB vs. ArangoDB vs. HugeGraph vs. Netezza

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonArangoDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  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 FlinkNative multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.A fast-speed and highly-scalable Graph DBMSData warehouse and analytics appliance part of IBM PureSystems
Primary database modelTime Series DBMSDocument store
Graph DBMS
Key-value store
Search engine
Graph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score3.26
Rank#88  Overall
#15  Document stores
#5  Graph DBMS
#12  Key-value stores
#10  Search engines
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websiteiotdb.apache.orgarangodb.comgithub.com/­hugegraph
hugegraph.apache.org
www.ibm.com/­products/­netezza
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.arangodb.comhugegraph.apache.org/­docs
Social network pagesLinkedInTwitterYouTubeFacebookInstagram
DeveloperApache Software FoundationArangoDB Inc.BaiduIBM
Initial release2018201220182000
Current release1.1.0, April 20233.11.5, November 20230.9
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial license (Enterprise) availableOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
Linux
macOS
Unix
Linux infoincluded in appliance
Data schemeyesschema-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.nono
Secondary indexesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLSQL-like query languagenonoyes
APIs and other access methodsJDBC
Native API
AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust
Groovy
Java
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyesJavaScriptasynchronous Gremlin script jobsyes
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infosince version 2.0yes 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 replicasSource-replica replication with configurable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkno infocan be done with stored procedures in JavaScriptvia hugegraph-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency infoconfigurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)
Eventual Consistency
Foreign keys infoReferential integritynoyes inforelationships in graphsyes infoedges in graphno
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.yesyes
User concepts infoAccess controlyesyesUsers, roles and permissionsUsers with fine-grained authorization concept
More information provided by the system vendor
Apache IoTDBArangoDBHugeGraphNetezza infoAlso called PureData System for Analytics by IBM
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 IoTDBArangoDBHugeGraphNetezza infoAlso called PureData System for Analytics by IBM
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