DBMS > CrateDB vs. Graph Engine vs. NuoDB vs. Oracle Berkeley DB

System Properties Comparison CrateDB vs. Graph Engine vs. NuoDB vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

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

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Widely used in-process key-value store

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Graph DBMS
Key-value store

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Relational DBMS

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

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.87
Rank	#201	Overall
	#94	Relational DBMS

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

Website

cratedb.com

www.graphengine.io

www.3ds.com/nuodb-distributed-sql-database

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

Technical documentation

cratedb.com/docs

www.graphengine.io/docs/manual

doc.nuodb.com

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

Developer

Crate

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2013

2010

2013

1994

Current release

5.8.1, August 2024

18.1.40, May 2020

License

Commercial or Open Source

Open Source

MIT License

commercial

limited edition free

Open Source

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.

Implementation language

Java

.NET and C

C++

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

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

.NET

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

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

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

SQL interfaced based on SQLite is available

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

C#
C++
F#
Visual Basic

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

.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

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

Java, SQL

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

data is dynamically stored/cached on the nodes where it is read/written

none

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes

Managed transparently by NuoDB

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

In-memory capabilities

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

yes

Temporary table

yes

User concepts

Access control

rights management via user accounts

Standard SQL roles/ privileges, Administrative Users

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More resources

DB-Engines blog posts

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