DBMS > Amazon Redshift vs. atoti vs. Datomic vs. eXtremeDB vs. NSDb

System Properties Comparison Amazon Redshift vs. atoti vs. Datomic vs. eXtremeDB vs. NSDb

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

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

Primary database model

Relational DBMS

Object oriented DBMS

Relational DBMS

Relational DBMS
Time Series 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	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

docs.atoti.io

docs.datomic.com

www.mcobject.com/docs/extremedb.htm

nsdb.io/Architecture

Developer

Amazon (based on PostgreSQL)

ActiveViam

Cognitect

McObject

Initial release

2012

2001

2017

Current release

1.0.6735, June 2023

8.2, 2021

License

Commercial or Open Source

commercial

free versions available

commercial

limited edition free

commercial

Open Source

Apache Version 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

Java

Java, Clojure

C and C++

Java, Scala

Server operating systems

hosted

All OS with a Java VM

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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.

support of XML interfaces available

Secondary indexes

restricted

yes

all fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

Multidimensional Expressions (MDX)

yes

with the option: eXtremeSQL

SQL-like query language

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

.Net
C
C#
C++
Java
Lua
Python
Scala

Java
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

Python

yes

Transaction Functions

yes

Triggers

By using transaction functions

yes

by defining events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

none

But extensive use of caching in the application peers

horizontal partitioning / sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

yes, multi-version concurrency control (MVCC)

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

Durability

Support for making data persistent

yes

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

yes

Using Apache Lucene

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

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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