DBMS > Amazon Redshift vs. Drizzle vs. EventStoreDB vs. GridGain

System Properties Comparison Amazon Redshift vs. Drizzle vs. EventStoreDB vs. GridGain

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

GridGain is an in-memory computing platform, built on Apache Ignite

Primary database model

Relational DBMS

Event Store

Key-value store
Relational DBMS

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	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Website

aws.amazon.com/redshift

www.eventstore.com

www.gridgain.com

Technical documentation

docs.aws.amazon.com/redshift

developers.eventstore.com

www.gridgain.com/docs/index.html

Developer

Amazon (based on PostgreSQL)

Drizzle project, originally started by Brian Aker

Event Store Limited

GridGain Systems, Inc.

Initial release

2012

2008

2012

2007

Current release

7.2.4, September 2012

21.2, February 2021

GridGain 8.5.1

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

commercial

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++

Java, C++, .Net

Server operating systems

hosted

FreeBSD
Linux
OS X

Linux
Windows

Linux
OS X
Solaris
Windows

Data scheme

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

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with proprietary extensions

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

JDBC
ODBC

JDBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes (compute grid and cache interceptors can be used instead)

Triggers

hooks for callbacks inside the server can be used.

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Security Hooks for custom implementations

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