DBMS > KeyDB vs. ObjectBox vs. Oracle Berkeley DB vs. SQream DB vs. Trafodion

System Properties Comparison KeyDB vs. ObjectBox vs. Oracle Berkeley DB vs. SQream DB vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Extremely fast embedded database for small devices, IoT and Mobile

Widely used in-process key-value store

a GPU-based, columnar RDBMS for big data analytics workloads

Transactional SQL-on-Hadoop DBMS

Primary database model

Key-value store

Object oriented DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

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

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

github.com/Snapchat/KeyDB
keydb.dev

objectbox.io

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

sqream.com

trafodion.apache.org

Technical documentation

docs.keydb.dev

docs.objectbox.io

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

docs.sqream.com

trafodion.apache.org/documentation.html

Developer

EQ Alpha Technology Ltd.

ObjectBox Limited

Oracle

originally developed by Sleepycat, which was acquired by Oracle

SQream Technologies

Apache Software Foundation, originally developed by HP

Initial release

2019

2017

1994

2017

2014

Current release

18.1.40, May 2020

2022.1.6, December 2022

2.3.0, February 2019

License

Commercial or Open Source

Open Source

BSD-3

Open Source

Apache License 2.0

Open Source

commercial license available

commercial

Open Source

Apache 2.0

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

C++

C and C++

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

C++, CUDA, Haskell, Java, Scala

C++, Java

Server operating systems

Linux

Android
iOS
Linux
macOS
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

yes, ANSI Standard SQL Types

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

by using the Redis Search module

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protoco

Proprietary native API

.Net
JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

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
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
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++
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Lua

user defined functions in Python

Java Stored Procedures

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

online/offline synchronization between client and server

Source-replica replication

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

simple password-based access control and ACL

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

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