DBMS > Amazon Redshift vs. Drizzle vs. Memcached vs. SQream DB vs. Sqrrl

System Properties Comparison Amazon Redshift vs. Drizzle vs. Memcached vs. SQream DB vs. Sqrrl

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.

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed 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.

In-memory key-value store, originally intended for caching

a GPU-based, columnar RDBMS for big data analytics workloads

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

aws.amazon.com/redshift

www.memcached.org

sqream.com

sqrrl.com

Technical documentation

docs.aws.amazon.com/redshift

github.com/memcached/memcached/wiki

docs.sqream.com

Developer

Amazon (based on PostgreSQL)

Drizzle project, originally started by Brian Aker

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

SQream Technologies

Amazon

originally Sqrrl Data, Inc.

Initial release

2012

2008

2003

2017

2012

Current release

7.2.4, September 2012

1.6.27, May 2024

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

BSD license

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C++, CUDA, Haskell, Java, Scala

Java

Server operating systems

hosted

FreeBSD
Linux
OS X

FreeBSD
Linux
OS X
Unix
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

JDBC

Proprietary protocol

.Net
JDBC
ODBC

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions in Python

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal and vertical partitioning

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

none

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

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

Atomic updates per row, document, or graph entity

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

yes

using SASL (Simple Authentication and Security Layer) protocol

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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