DBMS > Amazon DynamoDB vs. Brytlyt vs. IBM Db2 Event Store vs. Postgres-XL

System Properties Comparison Amazon DynamoDB vs. Brytlyt vs. IBM Db2 Event Store vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Distributed Event Store optimized for Internet of Things use cases

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store
Key-value store

Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	77.57
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	0.38
Rank	#279	Overall
	#126	Relational DBMS

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Website

aws.amazon.com/dynamodb

brytlyt.io

www.ibm.com/products/db2-event-store

www.postgres-xl.org

Technical documentation

docs.aws.amazon.com/dynamodb

docs.brytlyt.io

www.ibm.com/docs/en/db2-event-store

www.postgres-xl.org/documentation

Developer

Amazon

Brytlyt

IBM

Initial release

2012

2016

2017

2014

since 2012, originally named StormDB

Current release

5.0, August 2023

2.0

10 R1, October 2018

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free developer edition available

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++ and CUDA

C and C++

Server operating systems

hosted

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

specific XML-type available, but no XML query functionality.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Active-active shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID across one or more tables within a single AWS account and region

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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