DBMS > Drizzle vs. NuoDB vs. Tarantool vs. TerminusDB

System Properties Comparison Drizzle vs. NuoDB vs. Tarantool vs. TerminusDB

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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.

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

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Graph DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

Document store
RDF store

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

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

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

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

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

www.tarantool.io

terminusdb.com

Technical documentation

doc.nuodb.com

www.tarantool.io/en/doc

terminusdb.github.io/terminusdb/#

Developer

Drizzle project, originally started by Brian Aker

Dassault Systèmes

originally NuoDB, Inc.

DataChemist Ltd.

Initial release

2008

2013

2008

2018

Current release

7.2.4, September 2012

2.10.0, May 2022

11.0.0, January 2023

License

Commercial or Open Source

Open Source

GNU GPL

commercial

limited edition free

Open Source

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

Open Source

GPL V3

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++

Prolog, Rust

Server operating systems

FreeBSD
Linux
OS X

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

BSD
Linux
macOS

Linux

Data scheme

yes

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

yes

Typing

predefined data types such as float or date

yes

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

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

with proprietary extensions

yes

Full-featured ANSI SQL support

SQL-like query language (WOQL)

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

Open binary protocol

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
C++
Java
PHP

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

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

JavaScript
Python

Server-side scripts

Stored procedures

Java, SQL

Lua, C and SQL stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

yes

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

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

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

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Managed transparently by NuoDB

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

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

yes, write ahead logging

yes

in-memory journaling

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

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

Role-based access control

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