DBMS > Amazon Redshift vs. CockroachDB vs. FatDB vs. NCache vs. OpenTSDB

System Properties Comparison Amazon Redshift vs. CockroachDB vs. FatDB vs. NCache vs. OpenTSDB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Large scale data warehouse service for use with business intelligence tools

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

Scalable Time Series DBMS based on HBase

Primary database model

Relational DBMS

Document store
Key-value store

Key-value store

Time Series DBMS

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	6.15
Rank	#55	Overall
	#33	Relational DBMS

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

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Website

aws.amazon.com/redshift

www.cockroachlabs.com

www.alachisoft.com/ncache

opentsdb.net

Technical documentation

docs.aws.amazon.com/redshift

www.cockroachlabs.com/docs

www.alachisoft.com/resources/docs

opentsdb.net/docs/build/html/index.html

Developer

Amazon (based on PostgreSQL)

Cockroach Labs

FatCloud

Alachisoft

currently maintained by Yahoo and other contributors

Initial release

2012

2015

2012

2005

2011

Current release

23.1.1, May 2023

5.3.3, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0, commercial license available

commercial

Open Source

Enterprise Edition available

Open Source

LGPL

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

Java

Server operating systems

hosted

Linux
macOS
Windows

Windows

Linux
Windows

Data scheme

yes

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

partial

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

numeric data for metrics, strings for tags

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, wire compatible with PostgreSQL

Via inetgration in SQL Server

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

APIs and other access methods

JDBC
ODBC

JDBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

IDistributedCache
JCache
LINQ
Proprietary native API

HTTP API
Telnet API

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

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

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

via applications

support for stored procedures with SQL-Server CLR

Triggers

yes

via applications

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

yes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using RAFT

selectable replication factor

yes, with selectable consistency level

selectable replication factor

based on HBase

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

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

Immediate Consistency

based on HBase

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

optimistic locking and pessimistic locking

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

Role-based access control

Can implement custom security layer via applications

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

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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