DBMS > Tarantool vs. Teradata vs. VelocityDB vs. YottaDB

System Properties Comparison Tarantool vs. Teradata vs. VelocityDB vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

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

A hybrid cloud data analytics software platform (Teradata Vantage)

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

A fast and solid embedded Key-value store

Primary database model

Document store
Key-value store
Relational DBMS

Relational DBMS

Graph DBMS
Object oriented DBMS

Key-value store

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

Relational DBMS

using the Octo plugin

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

Score	1.63
Rank	#139	Overall
	#25	Document stores
	#24	Key-value stores
	#65	Relational DBMS

Score	41.47
Rank	#22	Overall
	#15	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS
	#21	Object oriented DBMS

Score	0.21
Rank	#309	Overall
	#43	Key-value stores

Website

Technical documentation

www.tarantool.io/en/doc

docs.teradata.com

velocitydb.com/UserGuide

yottadb.com/resources/documentation

Developer

Teradata

VelocityDB Inc

YottaDB, LLC

Initial release

2008

1984

2011

2001

Current release

2.10.0, May 2022

Teradata Vantage 1.0 MU2, January 2019

7.x

License

Commercial or Open Source

Open Source

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

commercial

Open Source

AGPL 3.0

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 and C++

Server operating systems

BSD
Linux
macOS

hosted
Linux

Any that supports .NET

Docker
Linux

Data scheme

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

yes

schema-free

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

yes

SQL

Support of SQL

Full-featured ANSI SQL support

yes

SQL 2016 + extensions

by using the Octo plugin

APIs and other access methods

Open binary protocol

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

.Net

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

.Net

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Lua, C and SQL stored procedures

yes

UDFs, stored procedures, table functions in parallel

Triggers

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

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes, write ahead logging

yes

In-memory capabilities

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

yes, full featured in-memory storage engine with persistence

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

Based on Windows Authentication

Users and groups based on OS-security mechanisms

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More resources

DB-Engines blog posts

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

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Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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