DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon Aurora vs. Hazelcast vs. IBM Db2 Event Store vs. Postgres-XL vs. Spark SQL

System Properties Comparison Amazon Aurora vs. Hazelcast vs. IBM Db2 Event Store vs. Postgres-XL vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use casesBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeEvent Store
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorahazelcast.comwww.ibm.com/­products/­db2-event-storewww.postgres-xl.orgspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlhazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-storewww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonHazelcastIBMApache Software Foundation
Initial release2015200820172014 infosince 2012, originally named StormDB2014
Current release5.3.6, November 20232.010 R1, October 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition availableOpen Source infoMozilla public licenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++CScala
Server operating systemshostedAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
macOS
Linux
OS X
Windows
Data schemeyesschema-freeyesyesyes
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.yesyes infothe object must implement a serialization strategynoyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLyesSQL-like query languageyes infothrough the embedded Spark runtimeyes infodistributed, parallel query executionSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesyesuser defined functionsno
Triggersyesyes infoEventsnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated MapActive-active shard replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednoACID infoMVCCno
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon AuroraHazelcastIBM Db2 Event StorePostgres-XLSpark SQL
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

show all

Recent citations in the news

Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ...
14 May 2024, AWS Blog

Join the preview of Amazon Aurora Limitless Database | Amazon Web Services
27 November 2023, AWS Blog

New – Amazon Aurora Optimized Reads for Aurora PostgreSQL with up to 8x query latency improvement for I/O ...
8 November 2023, AWS Blog

Knowledge Bases for Amazon Bedrock now supports Amazon Aurora PostgreSQL and Cohere embedding models ...
12 February 2024, AWS Blog

Improve the performance of generative AI workloads on Amazon Aurora with Optimized Reads and pgvector | Amazon ...
9 February 2024, AWS Blog

provided by Google News

Hazelcast Showcases Real-Time Data Platform at 2024 Gartner Summit
15 May 2024, Datanami

Hazelcast Weaves Wider Logic Threads Through The Data Fabric
7 March 2024, Forbes

Hazelcast to Demonstrate Power of Unified Platform for Real-Time and AI Applications at the ...
13 May 2024, WDRB

Hazelcast 5.4 real time data processing platform boosts AI and consistency
17 April 2024, VentureBeat

Real-Time Data Platform Hazelcast Introduces New Chief Technology Officer Adrian Soars
7 November 2023, Finovate

provided by Google News

The vision for Db2
26 February 2019, biplatform.nl

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, ibm.com

IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere
31 May 2018, Data Center Knowledge

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

Best cloud databases of 2022
4 October 2022, ITPro

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Feature Engineering for Time-Series Using PySpark on Databricks
8 May 2024, Towards Data Science

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here