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DBMS > AlaSQL vs. Apache IoTDB vs. Drizzle vs. H2 vs. Microsoft Access

System Properties Comparison AlaSQL vs. Apache IoTDB vs. Drizzle vs. H2 vs. Microsoft Access

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonApache IoTDB  Xexclude from comparisonDrizzle  Xexclude from comparisonH2  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionJavaScript DBMS libraryAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.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.)
Primary database modelDocument store
Relational DBMS
Time Series DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#260  Overall
#40  Document stores
#121  Relational DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Websitealasql.orgiotdb.apache.orgwww.h2database.comwww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationgithub.com/­AlaSQL/­alasqliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.h2database.com/­html/­main.htmldeveloper.microsoft.com/­en-us/­access
DeveloperAndrey Gershun & Mathias R. WulffApache Software FoundationDrizzle project, originally started by Brian AkerThomas MuellerMicrosoft
Initial release20142018200820051992
Current release1.1.0, April 20237.2.4, September 20122.2.220, July 20231902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoMIT-LicenseOpen Source infoApache Version 2.0Open Source infoGNU GPLOpen Source infodual-licence (Mozilla public license, Eclipse public license)commercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptJavaC++JavaC++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)All OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
All OS with a Java VMWindows infoNot a real database server, but making use of DLLs
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or datenoyesyesyesyes
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.nonono
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.SQL-like query languageyes infowith proprietary extensionsyesyes infobut not compliant to any SQL standard
APIs and other access methodsJavaScript APIJDBC
Native API
JDBCJDBC
ODBC
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesJavaScriptC
C#
C++
Go
Java
Python
Scala
C
C++
Java
PHP
JavaC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresnoyesnoJava Stored Procedures and User-Defined Functionsyes infosince Access 2010 using the ACE-engine
Triggersyesyesno infohooks for callbacks inside the server can be used.yesyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
With clustering: 2 database servers on different computers operate on identical copies of a databasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storagenoACIDACIDACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyesyesyes infobut no files for transaction logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlnoyesPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardno infoa simple user-level security was built in till version Access 2003

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More resources
AlaSQLApache IoTDBDrizzleH2Microsoft Access
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