DBMS > CrateDB vs. EsgynDB vs. NuoDB vs. SQLite vs. Yaacomo

System Properties Comparison CrateDB vs. EsgynDB vs. NuoDB vs. SQLite vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Distributed Database based on Lucene

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Widely used embeddable, in-process RDBMS

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#10	Vector DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

cratedb.com

www.esgyn.cn

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

www.sqlite.org

yaacomo.com

Technical documentation

cratedb.com/docs

doc.nuodb.com

www.sqlite.org/docs.html

Developer

Crate

Esgyn

Dassault Systèmes

originally NuoDB, Inc.

Dwayne Richard Hipp

Q2WEB GmbH

Initial release

2013

2015

2013

2000

2009

Current release

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

commercial

limited edition free

Open Source

Public Domain

commercial

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

C++, Java

C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

server-less

Android
Linux
Windows

Data scheme

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

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

SQL-92 is not fully supported

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

All languages supporting JDBC/ODBC/ADO.Net

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions (Javascript)

Java Stored Procedures

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Multi-source replication between multi datacenters

yes

Managed transparently by NuoDB

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

via file-system locks

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

fine grained access rights according to SQL-standard

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