DBMS > Faircom EDGE vs. GigaSpaces vs. Redis vs. Sphinx

System Properties Comparison Faircom EDGE vs. GigaSpaces vs. Redis vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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

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.

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Key-value store
Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

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

Search engine

Secondary database models

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	0.02
Rank	#369	Overall
	#57	Key-value stores
	#156	Relational DBMS

Score	0.94
Rank	#194	Overall
	#33	Document stores
	#7	Object oriented DBMS

Score	148.64
Rank	#6	Overall
	#1	Key-value stores

Score	5.92
Rank	#57	Overall
	#6	Search engines

Website

www.faircom.com/products/faircom-edge

www.gigaspaces.com

redis.com
redis.io

sphinxsearch.com

Technical documentation

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

docs.gigaspaces.com/latest/landing.html

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

sphinxsearch.com/docs

Developer

FairCom Corporation

Gigaspaces Technologies

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Sphinx Technologies Inc.

Initial release

1979

2000

2009

2001

Current release

V3, October 2020

15.5, September 2020

7.2.5, May 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache Version 2; Commercial licenses available

Open Source

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

Open Source

GPL version 2, commercial licence available

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.

Implementation language

ANSI C, C++

Java, C++, .Net

C++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Linux
macOS
Solaris
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

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

XML can be used for describing objects metadata

Secondary indexes

yes

with RediSearch module

yes

full-text index on all search fields

SQL

Support of SQL

yes

ANSI SQL queries

SQL-99 for query and DML statements

with RediSQL module

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

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

proprietary protocol

RESP - REdis Serialization Protocol

Proprietary protocol

Supported programming languages

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

.Net
C++
Java
Python
Scala

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

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

Triggers

yes

yes, event driven architecture

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

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

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

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

none

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
Tunable Consistency

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

yes

when using SQL

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

across SQL and NoSQL

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

The original contents of fields are not stored in the Sphinx index.

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 user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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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