DBMS > Amazon Redshift vs. EXASOL vs. Microsoft Azure Table Storage vs. NCache vs. TigerGraph

System Properties Comparison Amazon Redshift vs. EXASOL vs. Microsoft Azure Table Storage vs. NCache vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A Wide Column Store for rapid development using massive semi-structured datasets

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

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

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

aws.amazon.com/redshift

www.exasol.com

azure.microsoft.com/en-us/services/storage/tables

www.alachisoft.com/ncache

www.tigergraph.com

Technical documentation

docs.aws.amazon.com/redshift

www.exasol.com/resources

www.alachisoft.com/resources/docs

docs.tigergraph.com

Developer

Amazon (based on PostgreSQL)

Exasol

Microsoft

Alachisoft

Initial release

2012

2000

2012

2005

2017

Current release

5.3.3, April 2024

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

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

C#, .NET, .NET Core, Java

C++

Server operating systems

hosted

Linux
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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

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

SQL-like query language (GSQL)

APIs and other access methods

JDBC
ODBC

.Net
JDBC
ODBC
WebSocket

RESTful HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

Java
Lua
Python
R

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

C++
Java

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

support for stored procedures with SQL-Server CLR

yes

Triggers

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graphs

Transaction concepts

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

ACID

optimistic locking

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

Access rights for users, groups and roles according to SQL-standard

Access rights based on private key authentication or shared access signatures

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

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

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Market metrics

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Licensing and pricing models

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