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DBMS > Apache IoTDB vs. Coveo vs. Graph Engine vs. HBase vs. Microsoft Azure Table Storage

System Properties Comparison Apache IoTDB vs. Coveo vs. Graph Engine vs. HBase vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCoveo  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Table Storage  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 FlinkAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineWide-column store based on Apache Hadoop and on concepts of BigTableA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelTime Series DBMSSearch engineGraph DBMS
Key-value store
Wide column storeWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score2.28
Rank#114  Overall
#11  Search engines
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Websiteiotdb.apache.orgwww.coveo.comwww.graphengine.iohbase.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.coveo.comwww.graphengine.io/­docs/­manualhbase.apache.org/­book.html
DeveloperApache Software FoundationCoveoMicrosoftApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoft
Initial release20182012201020082012
Current release1.1.0, April 20232.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMIT LicenseOpen Source infoApache version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava.NET and CJava
Server operating systemsAll OS with a Java VM (>= 1.8)hosted.NETLinux
Unix
Windows infousing Cygwin
hosted
Data schemeyeshybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyesyesyesoptions to bring your own types, AVROyes
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.nonononono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like query languagenononono
APIs and other access methodsJDBC
Native API
RESTful HTTP APIRESTful HTTP APIJava API
RESTful HTTP API
Thrift
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
Java
JavaScript
Python
C#
C++
F#
Visual Basic
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesnoyesyes infoCoprocessors in Javano
Triggersyesyesnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)yeshorizontal partitioningShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesMulti-source replication
Source-replica replication
yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoSingle row ACID (across millions of columns)optimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlyesgranular access controls, API key management, content filtersAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights based on private key authentication or shared access signatures

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More resources
Apache IoTDBCoveoGraph Engine infoformer name: TrinityHBaseMicrosoft Azure Table Storage
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