DBMS > Amazon Redshift vs. Graphite vs. H2GIS vs. Sqrrl

System Properties Comparison Amazon Redshift vs. Graphite vs. H2GIS vs. Sqrrl

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Editorial information provided by DB-Engines

Name

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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Spatial extension of H2

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Relational DBMS

Time Series DBMS

Spatial DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

aws.amazon.com/redshift

github.com/graphite-project/graphite-web

www.h2gis.org

sqrrl.com

Technical documentation

docs.aws.amazon.com/redshift

graphite.readthedocs.io

www.h2gis.org/docs/home

Developer

Amazon (based on PostgreSQL)

Chris Davis

CNRS

Amazon

originally Sqrrl Data, Inc.

Initial release

2012

2006

2013

2012

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

LGPL 3.0

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

Python

Java

Server operating systems

hosted

Linux
Unix

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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

APIs and other access methods

JDBC
ODBC

HTTP API
Sockets

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

JavaScript (Node.js)
Python

Java

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

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

based on H2

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

none

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

locking

yes, multi-version concurrency control (MVCC)

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

yes

based on H2

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

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