DBMS > DolphinDB vs. Firebase Realtime Database vs. GigaSpaces vs. Graph Engine vs. Redis

System Properties Comparison DolphinDB vs. Firebase Realtime Database vs. GigaSpaces vs. Graph Engine vs. Redis

Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Time Series DBMS

Document store

Document store
Object oriented DBMS

Values are user defined objects

Graph DBMS
Key-value 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

Relational DBMS

Graph DBMS
Search engine

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	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

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

Website

www.dolphindb.com

firebase.google.com/products/realtime-database

www.gigaspaces.com

www.graphengine.io

redis.com
redis.io

Technical documentation

docs.dolphindb.cn/en/help200/index.html

firebase.google.com/docs/database

docs.gigaspaces.com/latest/landing.html

www.graphengine.io/docs/manual

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

Developer

DolphinDB, Inc

Google

acquired by Google 2014

Gigaspaces Technologies

Microsoft

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2018

2012

2000

2010

2009

Current release

v2.00.4, January 2022

15.5, September 2020

7.2.5, May 2024

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

MIT License

Open Source

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

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.

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

Implementation language

C++

Java, C++, .Net

.NET and C

Server operating systems

Linux
Windows

hosted

Linux
macOS
Solaris
Windows

.NET

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

XML can be used for describing objects metadata

Secondary indexes

yes

with RediSearch module

SQL

Support of SQL

SQL-like query language

SQL-99 for query and DML statements

with RediSQL module

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

Android
iOS
JavaScript API
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

RESTful HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Java
JavaScript
Objective-C

.Net
C++
Java
Python
Scala

C#
C++
F#
Visual Basic

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

yes

limited functionality with using 'rules'

yes

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

Triggers

Callbacks are triggered when data changes

yes, event driven architecture

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

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

Map-Reduce pattern can be built with XAP task executors

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

yes

ACID

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Administrators, Users, Groups

yes, based on authentication and database rules

Role-based access control

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

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