DBMS > Amazon Redshift vs. Datomic vs. Kyligence Enterprise vs. NSDb vs. Raima Database Manager

System Properties Comparison Amazon Redshift vs. Datomic vs. Kyligence Enterprise vs. NSDb vs. Raima Database Manager

Editorial information provided by DB-Engines

Name

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

A distributed analytics engine for big data, built on top of Apache Kylin

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

RDBMS with a small footprint, either embedded into an application or used as a database server

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS
Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.46
Rank	#259	Overall
	#120	Relational DBMS
	#22	Time Series DBMS

Website

aws.amazon.com/redshift

www.datomic.com

kyligence.io/kyligence-enterprise

nsdb.io

raima.com

Technical documentation

docs.aws.amazon.com/redshift

docs.datomic.com

nsdb.io/Architecture

docs.raima.com

Developer

Amazon (based on PostgreSQL)

Cognitect

Kyligence, Inc.

Raima Inc.

Initial release

2012

2016

2017

1984

Current release

1.0.6735, June 2023

15, June 2021

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

Apache Version 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

Java, Clojure

Java

Java, Scala

Server operating systems

hosted

All OS with a Java VM

Linux

Linux
macOS

Android
HP-UX
Integrity RTOS
iOS
Linux
OS X
QNX
Solaris
VxWorks
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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.

Exporting/Importing of XML structures possible

Secondary indexes

restricted

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

Java
Scala

.Net
C
C++
Objective-C
PL/SQL

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Transaction Functions

yes

based on the ANSI/ISO SQL Persistent Stored Modules (PSM) specification

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

Source-replica replication

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

Immediate Consistency or Eventual Consistency depending on configuration

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

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

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

yes

Using Apache Lucene

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

More information provided by the system vendor

Specific characteristics

Raima Database Manager (RDM) is an embedded time-series database optimized to run...
» more

Competitive advantages

Decreased time-to-market Industry-standard interfaces & tools for making your job...
» more

Typical application scenarios

Typical use cases include: Internet of Things (IoT) Embedded In-Memory Database Time-Series...
» more

Key customers

Infor, ABB, The Boeing Company, BAE Systems, Dow Jones, Dun & Bradstreet, Fujitsu,...
» more

Market metrics

Over 30 000 applications developers worldwide have field-tested RDM products More...
» more

Licensing and pricing models

Just as the technical aspects of Raima Database Manager are flexible, so are the...
» more

News

Raima Unveils RaimaDB 16.0: Elevating Database Performance and User Experience
29 February 2024

Raima Announces Release of Raima Database Manager (RDM) v15, a Powerful Embedded Time Series Database
10 June 2021

Raima Announces Release of Raima Database Manager (RDM) v14.2, a Powerful IoT Edge Embedded Database
8 October 2020

Raima Joins BlackBerry QNX Channel Partner Program to Deliver Safety-Critical and Secure Software Solutions
1 October 2020

Raima Expands Their Reseller Network in Asia
19 May 2020

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.