DBMS > Amazon Redshift vs. EventStoreDB vs. XTDB

System Properties Comparison Amazon Redshift vs. EventStoreDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Industrial-strength, open-source database solution built from the ground up for event sourcing.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Event Store

Document store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

aws.amazon.com/redshift

www.eventstore.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.aws.amazon.com/redshift

developers.eventstore.com

www.xtdb.com/docs

Developer

Amazon (based on PostgreSQL)

Event Store Limited

Juxt Ltd.

Initial release

2012

2019

Current release

21.2, February 2021

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

MIT 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

Clojure

Server operating systems

hosted

Linux
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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