DBMS > Datomic vs. DuckDB vs. RocksDB vs. Trino vs. Yanza

System Properties Comparison Datomic vs. DuckDB vs. RocksDB vs. Trino vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

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

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

Time Series DBMS for IoT Applications

Primary database model

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	4.57
Rank	#74	Overall
	#40	Relational DBMS

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

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

yanza.com

Technical documentation

docs.datomic.com

duckdb.org/docs

github.com/facebook/rocksdb/wiki

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

Social network pages

Developer

Cognitect

Facebook, Inc.

Trino Software Foundation

Yanza

Initial release

2012

2018

2013

2012

2020 rebranded from PrestoSQL

2015

Current release

1.0.6735, June 2023

0.10, February 2024

8.11.4, April 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

MIT License

Open Source

BSD

Open Source

Apache Version 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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

server-less

Linux

Linux
macOS

for devlopment

Windows

Data scheme

yes

schema-free

yes

schema-free

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.

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

C++ API
Java API

JDBC
RESTful HTTP API
Trino CLI

HTTP API

Supported programming languages

Clojure
Java

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

C
C++
Go
Java
Perl
Python
Ruby

Go
Java
JavaScript (Node.js)
Python
R
Ruby

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Transaction Functions

yes, depending on connected data-source

Triggers

By using transaction functions

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

horizontal partitioning

depending on connected data-source

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

yes

depending on connected data-source

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on connected data-source

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

yes

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

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

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

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

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.