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DBMS > Apache IoTDB vs. EDB Postgres vs. Google Cloud Datastore vs. Ingres

System Properties Comparison Apache IoTDB vs. EDB Postgres vs. Google Cloud Datastore vs. Ingres

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEDB Postgres  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIngres  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 EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWell established RDBMS
Primary database modelTime Series DBMSRelational DBMSDocument storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.91
Rank#130  Overall
#60  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Websiteiotdb.apache.orgwww.enterprisedb.comcloud.google.com/­datastorewww.actian.com/­databases/­ingres
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.enterprisedb.com/­docscloud.google.com/­datastore/­docsdocs.actian.com/­ingres
DeveloperApache Software FoundationEnterpriseDBGoogleActian Corporation
Initial release2018200520081974 infooriginally developed at University Berkely in early 1970s
Current release1.1.0, April 202314, December 202111.2, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoBSD for PostgreSQL-componentscommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
hostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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.noyes infospecific XML-type available, but no XML query functionality.nono infobut tools for importing/exporting data from/to XML-files available
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyes infostandard with numerous extensionsSQL-like query language (GQL)yes
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.using Google App Engineyes
TriggersyesyesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning infoby hash, list or rangeShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneously
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 replicationMulti-source replication using PaxosIngres Replicator
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate 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 integritynoyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes infoMVCC
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.yesnonono
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Apache IoTDBEDB PostgresGoogle Cloud DatastoreIngres
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