DBMS > Amazon Redshift vs. Brytlyt vs. Datomic vs. Machbase Neo

System Properties Comparison Amazon Redshift vs. Brytlyt vs. Datomic vs. Machbase Neo

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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

TimeSeries DBMS for AIoT and BigData

Primary database model

Relational DBMS

Time Series DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.27
Rank	#292	Overall
	#132	Relational DBMS

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Website

aws.amazon.com/redshift

brytlyt.io

www.datomic.com

machbase.com

Technical documentation

docs.aws.amazon.com/redshift

docs.brytlyt.io

docs.datomic.com

machbase.com/dbms

Developer

Amazon (based on PostgreSQL)

Brytlyt

Cognitect

Machbase

Initial release

2012

2016

2012

2013

Current release

5.0, August 2023

1.0.7180, July 2024

V8.0, August 2023

License

Commercial or Open Source

commercial

limited edition free

commercial

free test version available

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

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM

Linux
macOS
Windows

Data scheme

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.

yes

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

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

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

RESTful HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Clojure
Java

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

in PL/pgSQL

yes

Transaction Functions

Triggers

yes

By using transaction functions

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

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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)

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

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

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