DBMS > Amazon Redshift vs. Hazelcast vs. OrientDB vs. Sqrrl

System Properties Comparison Amazon Redshift vs. Hazelcast vs. OrientDB 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

A widely adopted in-memory data grid

Multi-model DBMS (Document, Graph, Key/Value)

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Relational DBMS

Key-value store

Document store
Graph DBMS
Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Website

aws.amazon.com/redshift

hazelcast.com

orientdb.org

sqrrl.com

Technical documentation

docs.aws.amazon.com/redshift

hazelcast.org/imdg/docs

www.orientdb.com/docs/last/index.html

Developer

Amazon (based on PostgreSQL)

Hazelcast

OrientDB LTD; CallidusCloud; SAP

Amazon

originally Sqrrl Data, Inc.

Initial release

2012

2008

2010

2012

Current release

5.3.6, November 2023

3.2.29, March 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache version 2

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

Java

Server operating systems

hosted

All OS with a Java VM

All OS with a Java JDK (>= JDK 6)

Linux

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

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

the object must implement a serialization strategy

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

SQL-like query language, no joins

APIs and other access methods

JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

Event Listeners, Executor Services

Java, Javascript

Triggers

yes

Events

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Multi-source replication

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

relationship in graphs

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

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

Role-based access control

Access rights for users and roles; record level security configurable

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

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