DBMS > Riak KV vs. SAP Advantage Database Server vs. Teradata vs. Trino

System Properties Comparison Riak KV vs. SAP Advantage Database Server vs. Teradata vs. Trino

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Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed, fault tolerant key-value store

Low-cost RDBMS with access to ISAM and FoxPro data structures

A hybrid cloud data analytics software platform (Teradata Vantage)

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Website

www.sap.com/products/advantage-database-server.html

www.teradata.com

trino.io

Technical documentation

www.tiot.jp/riak-docs/riak/kv/latest

docs.teradata.com

trino.io/broadcast
trino.io/docs/current

Social network pages

Developer

OpenSource, formerly Basho Technologies

Sybase, SAP

Teradata

Trino Software Foundation

Initial release

2009

1993

1984

2012

2020 rebranded from PrestoSQL

Current release

3.2.0, December 2022

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache version 2, commercial enterprise edition

commercial

Open Source

Apache Version 2.0

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.

Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

Erlang

Java

Server operating systems

Linux
OS X

Linux
Windows

hosted
Linux

Linux
macOS

for devlopment

Data scheme

schema-free

yes

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

Secondary indexes

restricted

yes

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

depending on connected data-source

SQL

Support of SQL

yes

SQL 2016 + extensions

yes

APIs and other access methods

HTTP API
Native Erlang Interface

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

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

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Delphi
Perl
PHP

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

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

Erlang

yes

UDFs, stored procedures, table functions in parallel

yes, depending on connected data-source

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

Hashing

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

Multi-source replication
Source-replica replication

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

links between data sets can be stored

yes

Transaction concepts

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

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

depending on connected data-source

In-memory capabilities

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

caching of (temporary) tables can be configured

yes

User concepts

Access control

yes, using Riak Security

fine grained access rights according to SQL-standard

SQL standard access control

More information provided by the system vendor

Specific characteristics

Trino is the fastest open source, massively parallel processing SQL query engine...
» more

Competitive advantages

High performance analtyics and data processing of very large data sets Powerful ANSI...
» more

Typical application scenarios

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more

Key customers

Trino is widely adopted across the globe as freely-available open source software....
» more

Market metrics

33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more

Licensing and pricing models

Trino is an open source project and usage is therefore free. Commercial offerings...
» more

News

60: Trino calling AI
22 May 2024

Big names round out the Trino Fest 2024 lineup
8 May 2024

59: Querying Trino with Java and jOOQ
24 April 2024

A sneak peek of Trino Fest 2024
15 April 2024

Time travel in Delta Lake connector
11 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

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

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Recent citations in the news

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