DBMS > Quasardb vs. Redis vs. TerminusDB

System Properties Comparison Quasardb vs. Redis vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

Distributed, high-performance timeseries database

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.

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

Primary database model

Time Series DBMS

Key-value store

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

Graph DBMS

Secondary database models

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

Document store
RDF store

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

Score	0.19
Rank	#327	Overall
	#30	Time Series DBMS

Score	156.44
Rank	#6	Overall
	#1	Key-value stores

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Website

quasar.ai

redis.com
redis.io

terminusdb.com

Technical documentation

doc.quasar.ai/master

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

terminusdb.github.io/terminusdb/#

Developer

quasardb

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

DataChemist Ltd.

Initial release

2009

2018

Current release

3.14.1, January 2024

7.2.4, January 2024

11.0.0, January 2023

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

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

Open Source

GPL V3

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

C++

Prolog, Rust

Server operating systems

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

partial

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

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

yes

with tags

yes

with RediSearch module

SQL

Support of SQL

SQL-like query language

with RediSQL module

SQL-like query language (WOQL)

APIs and other access methods

HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

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

JavaScript
Python

Server-side scripts

Stored procedures

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

yes

Triggers

publish/subscribe channels provide some trigger functionality; RedisGears

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

Sharding

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

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with selectable replication factor

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts and optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

in-memory journaling

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

Cryptographically strong user authentication and audit trail

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

Role-based access control

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