DBMS > Amazon Redshift vs. Brytlyt vs. Datomic vs. GigaSpaces vs. Prometheus

System Properties Comparison Amazon Redshift vs. Brytlyt vs. Datomic vs. GigaSpaces vs. Prometheus

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Open-source Time Series DBMS and monitoring system

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

docs.brytlyt.io

docs.datomic.com

docs.gigaspaces.com/latest/landing.html

prometheus.io/docs

Developer

Amazon (based on PostgreSQL)

Brytlyt

Cognitect

Gigaspaces Technologies

Initial release

2012

2016

2012

2000

2015

Current release

5.0, August 2023

1.0.6735, June 2023

15.5, September 2020

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

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++ and CUDA

Java, Clojure

Java, C++, .Net

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM

Linux
macOS
Solaris
Windows

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

specific XML-type available, but no XML query functionality.

XML can be used for describing objects metadata

Import of XML data possible

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-99 for query and DML statements

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Clojure
Java

.Net
C++
Java
Python
Scala

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

in PL/pgSQL

yes

Transaction Functions

yes

Triggers

yes

By using transaction functions

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

But extensive use of caching in the application peers

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

none

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

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

Role-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.