DBMS > Dragonfly vs. FoundationDB vs. Oracle Berkeley DB vs. Redis vs. ScyllaDB

System Properties Comparison Dragonfly vs. FoundationDB vs. Oracle Berkeley DB vs. Redis vs. ScyllaDB

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Ordered key-value store. Core features are complimented by layers.

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.

Cassandra and DynamoDB compatible wide column store

Primary database model

Key-value store

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

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

Wide column store

Secondary database models

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

Key-value store

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

Score	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	0.97
Rank	#191	Overall
	#32	Document stores
	#28	Key-value stores
	#87	Relational DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Score	149.43
Rank	#6	Overall
	#1	Key-value stores

Score	4.15
Rank	#69	Overall
	#5	Wide column stores

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

github.com/apple/foundationdb

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

redis.com
redis.io

www.scylladb.com

Technical documentation

www.dragonflydb.io/docs

apple.github.io/foundationdb

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

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

docs.scylladb.com

Developer

DragonflyDB team and community contributors

FoundationDB

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

ScyllaDB

Initial release

2023

2013

1994

2009

2015

Current release

1.0, March 2023

6.2.28, November 2020

18.1.40, May 2020

7.2.5, May 2024

ScyllaDB Open Source 6.0.2, July 2024

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache 2.0

Open Source

commercial license available

Open Source

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

Open Source

Open Source (AGPL), commercial license 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.

Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS

Implementation language

C++

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

C++

Server operating systems

Linux

Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

Data scheme

scheme-free

schema-free

some layers support schemas

schema-free

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

some layers support typing

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

with RediSearch module

yes

cluster global secondary indices

SQL

Support of SQL

supported in specific SQL layer only

yes

SQL interfaced based on SQLite is available

with RediSQL module

SQL-like DML and DDL statements (CQL)

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

proprietary protocol

RESP - REdis Serialization Protocol

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.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

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Server-side scripts

Stored procedures

Lua

in SQL-layer only

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

yes, Lua

Triggers

publish/subscribe channels provide some trigger functionality

yes

only for the SQL API

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Source-replica replication

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Linearizable consistency

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

in SQL-layer only

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Atomic execution of command blocks and scripts and optimistic locking

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

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

In-memory capabilities

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

yes

in-memory tables

User concepts

Access control

Password-based 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

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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