DBMS > Drizzle vs. EsgynDB vs. NuoDB vs. SQream DB vs. Tarantool

System Properties Comparison Drizzle vs. EsgynDB vs. NuoDB vs. SQream DB vs. Tarantool

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

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

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

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Website

www.esgyn.cn

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

sqream.com

www.tarantool.io

Technical documentation

doc.nuodb.com

docs.sqream.com

www.tarantool.io/en/doc

Developer

Drizzle project, originally started by Brian Aker

Esgyn

Dassault Systèmes

originally NuoDB, Inc.

SQream Technologies

Initial release

2008

2015

2013

2017

2008

Current release

7.2.4, September 2012

2022.1.6, December 2022

2.10.0, May 2022

License

Commercial or Open Source

Open Source

GNU GPL

commercial

limited edition free

commercial

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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++, Java

C++

C++, CUDA, Haskell, Java, Scala

C and C++

Server operating systems

FreeBSD
Linux
OS X

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux

BSD
Linux
macOS

Data scheme

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

string, double, decimal, uuid, integer, blob, boolean, datetime

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

with proprietary extensions

yes

Full-featured ANSI SQL support

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

.Net
JDBC
ODBC

Open binary protocol

Supported programming languages

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

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

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

Java Stored Procedures

Java, SQL

user defined functions in Python

Lua, C and SQL stored procedures

Triggers

hooks for callbacks inside the server can be used.

yes

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

horizontal and vertical partitioning

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

yes

Managed transparently by NuoDB

none

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

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

yes

Temporary table

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

show all

Meet some database management systems you are likely to hear more about in the future
4 August 2014, Paul Andlinger

show all

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

show all

Recent citations in the news

Dassault Systèmes Announces the Acquisition of NuoDB, a Cloud-Native Distributed SQL Database Leader
25 November 2020, Dassault Systèmes

Deploy the NuoDB Database in Docker Containers
16 October 2017, The New Stack

NuoDB set to improve distributed SQL performance
7 January 2020, TechTarget

Dassault Systemes to acquire U.S.-based NuoDB
25 November 2020, MarketWatch

Big Data Product Watch 1/31/17: No-Cost NuoDB, GPU Analytics, Cloud Object Storage, More -- ADTmag
31 January 2017, ADT Magazine

provided by Google News

SQream Announces Strategic Integration for Powerful Big Data Analytics with Dataiku
9 February 2024, insideBIGDATA

I SQream, you SQream, we all SQream for … data analytics?
5 October 2023, FierceWireless

SQream Joins Samsung Cloud Platform Ecosystem
26 July 2023, Datanami

GPU data warehouse startup SQream lands $39.4M funding round
24 June 2020, SiliconANGLE News

SQream Technologies raises $39.4 million for GPU-accelerated databases
24 June 2020, VentureBeat

provided by Google News

TaranHouse: New Big Data Warehouse Announced by Tarantool
4 April 2018, Newswire

In-Memory Showdown: Redis vs. Tarantool
4 April 2023, Хабр

Deploying Tarantool Cartridge applications with zero effort (Part 1)
16 December 2019, Хабр

Deploying Tarantool Cartridge applications with zero effort (Part 2)
13 April 2020, Хабр

Тarantool Cartridge: Sharding Lua Backend in Three Lines
9 October 2019, Хабр

provided by Google News

Share this page