DBMS > Amazon Redshift vs. Graph Engine vs. Newts vs. Rockset vs. Sqrrl

System Properties Comparison Amazon Redshift vs. Graph Engine vs. Newts vs. Rockset vs. Sqrrl

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Time Series DBMS based on Cassandra

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Time Series DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Relational DBMS
Search engine

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

aws.amazon.com/redshift

www.graphengine.io

opennms.github.io/newts

rockset.com

sqrrl.com

Technical documentation

docs.aws.amazon.com/redshift

www.graphengine.io/docs/manual

github.com/OpenNMS/newts/wiki

docs.rockset.com

Developer

Amazon (based on PostgreSQL)

Microsoft

OpenNMS Group

Rockset

Amazon

originally Sqrrl Data, Inc.

Initial release

2012

2010

2014

2019

2012

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache 2.0

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

.NET and C

Java

C++

Java

Server operating systems

hosted

.NET

Linux
OS X
Windows

hosted

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

restricted

all fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

HTTP REST
Java API

HTTP REST

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
F#
Visual Basic

Java

Go
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

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

based on Cassandra

Automatic sharding

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

yes

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

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

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent 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

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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

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