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DBMS > Apache IoTDB vs. Microsoft Access vs. Microsoft SQL Server vs. Titan vs. Vertica

System Properties Comparison Apache IoTDB vs. Microsoft Access vs. Microsoft SQL Server vs. Titan vs. Vertica

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonTitan  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
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 FlinkMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Microsofts flagship relational DBMSTitan is a Graph DBMS optimized for distributed clusters.Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelTime Series DBMSRelational DBMSRelational DBMSGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score824.29
Rank#3  Overall
#3  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteiotdb.apache.orgwww.microsoft.com/­en-us/­microsoft-365/­accesswww.microsoft.com/­en-us/­sql-servergithub.com/­thinkaurelius/­titanwww.vertica.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldeveloper.microsoft.com/­en-us/­accesslearn.microsoft.com/­en-US/­sql/­sql-servergithub.com/­thinkaurelius/­titan/­wikivertica.com/­documentation
DeveloperApache Software FoundationMicrosoftMicrosoftAurelius, owned by DataStaxOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20181992198920122005
Current release1.1.0, April 20231902 (16.0.11328.20222), March 2019SQL Server 2022, November 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoBundled with Microsoft Officecommercial inforestricted free version is availableOpen Source infoApache license, version 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageJavaC++C++JavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)Windows infoNot a real database server, but making use of DLLsLinux
Windows
Linux
OS X
Unix
Windows
Linux
Data schemeyesyesyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.noyesno
Secondary indexesyesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languageyes infobut not compliant to any SQL standardyesnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
Native API
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Clojure
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesyes infosince Access 2010 using the ACE-engineTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javayesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes infosince Access 2010 using the ACE-engineyesyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)nonetables can be distributed across several files (horizontal partitioning); sharding through federationyes infovia pluggable storage backendshorizontal partitioning, hierarchical 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 replicasnoneyes, but depending on the SQL-Server EditionyesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes infovia Faunus, a graph analytics engineno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesyes infoRelationships in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infobut no files for transaction loggingACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyesno infoa simple user-level security was built in till version Access 2003fine grained access rights according to SQL-standardUser authentification and security via Rexster Graph Serverfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache IoTDBMicrosoft AccessMicrosoft SQL ServerTitanVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Apache IoTDBMicrosoft AccessMicrosoft SQL ServerTitanVertica infoOpenText™ Vertica™
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