DBMS > Dgraph vs. EJDB vs. Redis

System Properties Comparison Dgraph vs. EJDB vs. Redis

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Graph DBMS

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

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	1.86
Rank	#156	Overall
	#14	Graph DBMS

Score	0.51
Rank	#281	Overall
	#43	Document stores

Score	162.96
Rank	#6	Overall
	#1	Key-value stores

Website

dgraph.io

github.com/Softmotions/ejdb

redis.com
redis.io

Technical documentation

dgraph.io/docs

github.com/Softmotions/ejdb/blob/master/README.md

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

Social network pages

Developer

Dgraph Labs, Inc.

Softmotions

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2016

2012

2009

Current release

7.2.1, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2

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.

Redis Enterprise Cloud: Instantly scale and pay only for the resources you need - on any cloud - AWS, Azure or Google Cloud.
Aiven for Redis: Fully managed in-memory key-value store, for all your caching and speedy lookup needs.

Implementation language

Server operating systems

Linux
OS X
Windows

server-less

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

Secondary indexes

yes

with RediSearch module

SQL

Support of SQL

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

in-process shared library

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

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

Triggers

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

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

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

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts and optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Data access is serialized by the server

Durability

Support for making data persistent

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

User concepts

Access control

Planned for future releases

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

The Redis real-time data platform builds upon the unmatched simplicity and speed...
» more

Competitive advantages

Redis Enterprise is a robust in-memory database platform built by the people who...
» more

Typical application scenarios

Redis Enterprise is used by large enterprise, startup, and government organizations...
» more

Key customers

Verizon, Vodafone, Atlassian, Trip Advisor, Jet.com, Nokia, Samsung, HTC, Docker,...
» more

Market metrics

Most launched Docker container per day according to Docker Hub (7.2M launches per...
» more

Licensing and pricing models

Redis Enterprise Cloud lets users scale up and down instantly, and pay only for the...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.