DBMS > Faircom EDGE vs. LevelDB vs. Microsoft Azure AI Search vs. Oracle Berkeley DB vs. Redis

System Properties Comparison Faircom EDGE vs. LevelDB vs. Microsoft Azure AI Search vs. Oracle Berkeley DB vs. Redis

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Search-as-a-service for web and mobile app development

Widely used in-process key-value store

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

Key-value store
Relational DBMS

Key-value store

Search engine

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

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

Secondary database models

Vector 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	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

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

Website

www.faircom.com/products/faircom-edge

github.com/google/leveldb

azure.microsoft.com/en-us/services/search

www.oracle.com/database/technologies/related/berkeleydb.html

redis.com
redis.io

Technical documentation

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

github.com/google/leveldb/blob/main/doc/index.md

learn.microsoft.com/en-us/azure/search

docs.oracle.com/cd/E17076_05/html/index.html

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

Developer

FairCom Corporation

Google

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

1979

2011

2015

1994

2009

Current release

V3, October 2020

1.23, February 2021

18.1.40, May 2020

7.2.4, January 2024

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

BSD

commercial

Open Source

commercial license available

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

ANSI C, C++

C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Illumos
Linux
OS X
Windows

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

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

schema-free

yes

schema-free

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

only with the Berkeley DB XML edition

Secondary indexes

yes

with RediSearch module

SQL

Support of SQL

yes

ANSI SQL queries

yes

SQL interfaced based on SQLite is available

with RediSQL module

APIs and other access methods

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

RESTful HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C#
Java
JavaScript
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

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

.Net, JavaScript, C/C++

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

Triggers

yes

only for the SQL API

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

none

Sharding

Implicit feature of the cloud service

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

Synchronous and asynchronous realtime replication based on transaction logs

none

yes

Implicit feature of the cloud service

Source-replica replication

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
Tunable Consistency

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

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

Durability

Support for making data persistent

yes

with automatic compression on writes

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

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

yes

using Azure authentication

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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