DBMS > Atos Standard Common Repository vs. NCache vs. QuestDB vs. RDF4J vs. Redis

System Properties Comparison Atos Standard Common Repository vs. NCache vs. QuestDB vs. RDF4J vs. Redis

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

A high performance open source SQL database for time series data

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

Primary database model

Document store
Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Secondary database models

Document store
Search engine

Using distributed Lucene

Relational DBMS

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

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

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

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	157.80
Rank	#6	Overall
	#1	Key-value stores

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.alachisoft.com/ncache

questdb.io

rdf4j.org

redis.com
redis.io

Technical documentation

www.alachisoft.com/resources/docs

questdb.io/docs

rdf4j.org/documentation

docs.redis.com/latest/index.html
redis.io/docs

Developer

Atos Convergence Creators

Alachisoft

QuestDB Technology Inc

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2016

2005

2014

2004

2009

Current release

1703

5.3.3, April 2024

7.2.4, January 2024

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Implementation language

Java

C#, .NET, .NET Core, Java

Java (Zero-GC), C++, Rust

Java

Server operating systems

Linux

Linux
Windows

Linux
macOS
Windows

Linux
OS X
Unix
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

schema-free via InfluxDB Line Protocol

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

optional

partial

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

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

yes

with RediSearch module

SQL

Support of SQL

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

SQL with time-series extensions

with RediSQL module

APIs and other access methods

LDAP

IDistributedCache
JCache
LINQ
Proprietary native API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

All languages with LDAP bindings

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

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Java
PHP
Python

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

support for stored procedures with SQL-Server CLR

yes

Lua; Redis Functions coming in Redis 7 (slides and Github)

Triggers

yes

Notifications

yes

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

yes

horizontal partitioning (by timestamps)

none

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with selectable consistency level

Source-replica replication with eventual consistency

none

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

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

Immediate Consistency

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

optimistic locking and pessimistic locking

ACID for single-table writes

ACID

Isolation support depends on the API used

Atomic execution of command blocks and scripts and optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities

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

yes

through memory mapped files

yes

User concepts

Access control

LDAP bind authentication

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

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

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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Market metrics

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

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