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DBMS > Apache IoTDB vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Riak KV vs. Sqrrl

System Properties Comparison Apache IoTDB vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Riak KV vs. Sqrrl

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed 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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully managed big data interactive analytics platformDistributed, fault tolerant key-value storeAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelTime Series DBMSGraph DBMS
Key-value store
Relational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexesDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score0.62
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score4.44
Rank#80  Overall
#9  Key-value stores
Websiteiotdb.apache.orgwww.graphengine.ioazure.microsoft.com/­services/­data-explorersqrrl.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software FoundationMicrosoftMicrosoftOpenSource, formerly Basho TechnologiesAmazon infooriginally Sqrrl Data, Inc.
Initial release20182010201920092012
Current release1.1.0, April 2023cloud service with continuous releases3.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT LicensecommercialOpen Source infoApache version 2, commercial enterprise editioncommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava.NET and CErlangJava
Server operating systemsAll OS with a Java VM (>= 1.8).NEThostedLinux
OS X
Linux
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyes
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 indexesyesall fields are automatically indexedrestrictedyes
SQL infoSupport of SQLSQL-like query languagenoKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsJDBC
Native API
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyesyesYes, possible languages: KQL, Python, RErlangno
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"Sharding infomaking use of Hadoop
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 infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factorselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynononono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyesAzure Active Directory Authenticationyes, using Riak SecurityCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Apache IoTDBGraph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerRiak KVSqrrl
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