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DBMS > Apache IoTDB vs. Databricks vs. Microsoft Access vs. Microsoft SQL Server vs. Sphinx

System Properties Comparison Apache IoTDB vs. Databricks vs. Microsoft Access vs. Microsoft SQL Server vs. Sphinx

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabricks  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonSphinx  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 FlinkThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Microsoft 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 DBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSDocument store
Relational DBMS
Relational DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score824.29
Rank#3  Overall
#3  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteiotdb.apache.orgwww.databricks.comwww.microsoft.com/­en-us/­microsoft-365/­accesswww.microsoft.com/­en-us/­sql-serversphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databricks.comdeveloper.microsoft.com/­en-us/­accesslearn.microsoft.com/­en-US/­sql/­sql-serversphinxsearch.com/­docs
DeveloperApache Software FoundationDatabricksMicrosoftMicrosoftSphinx Technologies Inc.
Initial release20182013199219892001
Current release1.1.0, April 20231902 (16.0.11328.20222), March 2019SQL Server 2022, November 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infoBundled with Microsoft Officecommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++C++
Server operating systemsAll OS with a Java VM (>= 1.8)hostedWindows infoNot a real database server, but making use of DLLsLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLyes infobut not compliant to any SQL standardyesSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Python
R
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
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesyes infosince Access 2010 using the ACE-engineTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
Triggersyesyes infosince Access 2010 using the ACE-engineyesno
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 federationSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesnoneyes, but depending on the SQL-Server Editionnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infobut no files for transaction loggingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlyesno infoa simple user-level security was built in till version Access 2003fine grained access rights according to SQL-standardno
More information provided by the system vendor
Apache IoTDBDatabricksMicrosoft AccessMicrosoft SQL ServerSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache IoTDBDatabricksMicrosoft AccessMicrosoft SQL ServerSphinx
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