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DBMS > Apache IoTDB vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Raima Database Manager

System Properties Comparison Apache IoTDB vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Raima Database Manager

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparisonRaima Database Manager infoformerly named db_Vista  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 FlinkFully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLRDBMS with a small footprint, either embedded into an application or used as a database server
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS
Time Series DBMS
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
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score0.49
Rank#259  Overall
#121  Relational DBMS
#21  Time Series DBMS
Websiteiotdb.apache.orgazure.microsoft.com/­services/­data-explorerwww.postgresql.orgraima.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docsdocs.raima.com
DeveloperApache Software FoundationMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerRaima Inc.
Initial release201820191989 info1989: Postgres, 1996: PostgreSQL1984
Current release1.1.0, April 2023cloud service with continuous releases16.3, May 202415, June 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC
Server operating systemsAll OS with a Java VM (>= 1.8)hostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Android
HP-UX
Integrity RTOS
iOS
Linux
OS X
QNX
Solaris
VxWorks
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.noyesyes infospecific XML-type available, but no XML query functionality.no infoExporting/Importing of XML structures possible
Secondary indexesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetyes infostandard with numerous extensionsyes
APIs and other access methodsJDBC
Native API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Objective-C
PL/SQL
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infobased on the ANSI/ISO SQL Persistent Stored Modules (PSM) specification
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hashhorizontal partitioning
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.Source-replica replication infoother methods possible by using 3rd party extensionsSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.yesnonoyes
User concepts infoAccess controlyesAzure Active Directory Authenticationfine grained access rights according to SQL-standardno
More information provided by the system vendor
Apache IoTDBMicrosoft Azure Data ExplorerPostgreSQLRaima Database Manager infoformerly named db_Vista
Specific characteristicsRaima Database Manager (RDM) is an embedded time-series database optimized to run...
» more
Competitive advantagesDecreased time-to-market Industry-standard interfaces & tools for making your job...
» more
Typical application scenariosTypical use cases include: Internet of Things (IoT) Embedded In-Memory Database Time-Series...
» more
Key customersInfor, ABB, The Boeing Company, BAE Systems, Dow Jones, Dun & Bradstreet, Fujitsu,...
» more
Market metricsOver 30 000 applications developers worldwide have field-tested RDM products More...
» more
Licensing and pricing modelsJust as the technical aspects of Raima Database Manager are flexible, so are the...
» more
News

Raima Unveils RaimaDB 16.0: Elevating Database Performance and User Experience
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Raima Announces Release of Raima Database Manager (RDM) v15, a Powerful Embedded Time Series Database
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8 October 2020

Raima Joins BlackBerry QNX Channel Partner Program to Deliver Safety-Critical and Secure Software Solutions
1 October 2020

Raima Expands Their Reseller Network in Asia
19 May 2020

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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