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DBMS > Apache IoTDB vs. Google Cloud Datastore vs. Kyligence Enterprise vs. Microsoft Access

System Properties Comparison Apache IoTDB vs. Google Cloud Datastore vs. Kyligence Enterprise vs. Microsoft Access

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonMicrosoft Access  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 FlinkAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA distributed analytics engine for big data, built on top of Apache KylinMicrosoft 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 modelTime Series DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score0.44
Rank#259  Overall
#118  Relational DBMS
Score93.76
Rank#12  Overall
#8  Relational DBMS
Websiteiotdb.apache.orgcloud.google.com/­datastorekyligence.io/­kyligence-enterprisewww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­access
DeveloperApache Software FoundationGoogleKyligence, Inc.Microsoft
Initial release2018200820161992
Current release1.1.0, April 20231902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinuxWindows infoNot a real database server, but making use of DLLs
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query language (GQL)ANSI SQL for queries (using Apache Calcite)yes infobut not compliant to any SQL standard
APIs and other access methodsJDBC
Native API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresyesusing Google App Engineyes infosince Access 2010 using the ACE-engine
TriggersyesCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yesnono
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no infoa simple user-level security was built in till version Access 2003

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More resources
Apache IoTDBGoogle Cloud DatastoreKyligence EnterpriseMicrosoft Access
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