DBMS > Amazon Redshift vs. BigObject vs. NCache vs. OpenEdge vs. TerminusDB

System Properties Comparison Amazon Redshift vs. BigObject vs. NCache vs. OpenEdge vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for real-time computations and queries

Open-Source and Enterprise in-memory Key-Value Store

Application development environment with integrated database management system

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Relational DBMS

Graph DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

Document store
RDF store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

aws.amazon.com/redshift

bigobject.io

www.alachisoft.com/ncache

www.progress.com/openedge

terminusdb.com

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

www.alachisoft.com/resources/docs

documentation.progress.com/output/ua/OpenEdge_latest

terminusdb.github.io/terminusdb/#

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

Alachisoft

Progress Software Corporation

DataChemist Ltd.

Initial release

2012

2015

2005

1984

2018

Current release

5.3.3, April 2024

OpenEdge 12.2, March 2020

11.0.0, January 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

Enterprise Edition available

commercial

Open Source

GPL V3

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#, .NET, .NET Core, Java

Prolog, Rust

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

close to SQL 92

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

All languages supporting JDBC/ODBC

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Progress proprietary ABL (Advanced Business Language)

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

support for stored procedures with SQL-Server CLR

yes

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

horizontal partitioning

since Version 11.4

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes, with selectable consistency level

Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

Users and groups

Role-based access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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