DBMS > Amazon Redshift vs. Datomic vs. Hawkular Metrics vs. Sphinx vs. Yaacomo

System Properties Comparison Amazon Redshift vs. Datomic vs. Hawkular Metrics vs. Sphinx vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Large scale data warehouse service for use with business intelligence tools

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Open source search engine for searching in data from different sources, e.g. relational databases

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

aws.amazon.com/redshift

www.datomic.com

www.hawkular.org

sphinxsearch.com

yaacomo.com

Technical documentation

docs.aws.amazon.com/redshift

docs.datomic.com

www.hawkular.org/hawkular-metrics/docs/user-guide

sphinxsearch.com/docs

Developer

Amazon (based on PostgreSQL)

Cognitect

Community supported by Red Hat

Sphinx Technologies Inc.

Q2WEB GmbH

Initial release

2012

2014

2001

2009

Current release

1.0.6735, June 2023

3.5.1, February 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache 2.0

Open Source

GPL version 2, commercial licence available

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

Java, Clojure

Java

C++

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Android
Linux
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

restricted

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language (SphinxQL)

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

HTTP REST

Proprietary protocol

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

Go
Java
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Transaction Functions

Triggers

By using transaction functions

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

based on Cassandra

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

selectable replication factor

based on Cassandra

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

The original contents of fields are not stored in the Sphinx index.

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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