DBMS > Datomic vs. RocksDB vs. Teradata Aster vs. Trino

System Properties Comparison Datomic vs. RocksDB vs. Teradata Aster vs. Trino

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Platform for big data analytics on multistructured data sources and types

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

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

www.datomic.com

rocksdb.org

trino.io

Technical documentation

docs.datomic.com

github.com/facebook/rocksdb/wiki

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

Social network pages

Developer

Cognitect

Facebook, Inc.

Teradata

Trino Software Foundation

Initial release

2012

2013

2005

2012

2020 rebranded from PrestoSQL

Current release

1.0.6735, June 2023

8.11.4, April 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

BSD

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

Java, Clojure

C++

Java

Server operating systems

All OS with a Java VM

Linux

Linux
macOS

for devlopment

Data scheme

yes

schema-free

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

C++ API
Java API

ADO.NET
JDBC
ODBC
OLE DB

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

Clojure
Java

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Java
Python
R

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

R packages

yes, depending on connected data-source

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

horizontal partitioning

Sharding

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

depending on connected data-source

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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.

yes

recommended only for testing and development

yes

User concepts

Access control

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...
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Typical application scenarios

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
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Key customers

Trino is widely adopted across the globe as freely-available open source software....
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Market metrics

33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
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Licensing and pricing models

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

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

58: Understanding your users with Trino and Mitzu
4 April 2024

57: Seeing clearly with OpenTelemetry
14 March 2024

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