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DBMS > Amazon DynamoDB vs. Apache IoTDB vs. EsgynDB vs. IBM Db2 Event Store vs. PostgreSQL

System Properties Comparison Amazon DynamoDB vs. Apache IoTDB vs. EsgynDB vs. IBM Db2 Event Store vs. PostgreSQL

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionDistributed Event Store optimized for Internet of Things use casesWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMSEvent Store
Time Series DBMS
Relational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.45
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Websiteaws.amazon.com/­dynamodbiotdb.apache.orgwww.esgyn.cnwww.ibm.com/­products/­db2-event-storewww.postgresql.org
Technical documentationdocs.aws.amazon.com/­dynamodbiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.ibm.com/­docs/­en/­db2-event-storewww.postgresql.org/­docs
DeveloperAmazonApache Software FoundationEsgynIBMPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release20122018201520171989 info1989: Postgres, 1996: PostgreSQL
Current release1.1.0, April 20232.016.3, May 2024
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache Version 2.0commercialcommercial infofree developer edition availableOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnononono
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Implementation languageJavaC++, JavaC and C++C
Server operating systemshostedAll OS with a Java VM (>= 1.8)LinuxLinux infoLinux, macOS, Windows for the developer additionFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeschema-freeyesyesyesyes
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.nononoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLnoSQL-like query languageyesyes infothrough the embedded Spark runtimeyes infostandard with numerous extensions
APIs and other access methodsRESTful HTTP APIJDBC
Native API
ADO.NET
JDBC
ODBC
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C
C#
C++
Go
Java
Python
Scala
All languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoyesJava Stored Proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersyes infoby integration with AWS Lambdayesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication between multi datacentersActive-active shard replicationSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Integration with Hadoop and Sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Amazon DynamoDBApache IoTDBEsgynDBIBM Db2 Event StorePostgreSQL
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