DBMS > Datomic vs. Dragonfly vs. Snowflake vs. Trino

System Properties Comparison Datomic vs. Dragonfly vs. Snowflake vs. Trino

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Editorial information provided by DB-Engines

Name

Description

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Cloud-based data warehousing service for structured and semi-structured data

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	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

www.datomic.com

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.snowflake.com

trino.io

Technical documentation

docs.datomic.com

www.dragonflydb.io/docs

docs.snowflake.net/manuals/index.html

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

Social network pages

Developer

Cognitect

DragonflyDB team and community contributors

Snowflake Computing Inc.

Trino Software Foundation

Initial release

2012

2023

2014

2012

2020 rebranded from PrestoSQL

Current release

1.0.6735, June 2023

1.0, March 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

BSL 1.1

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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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

hosted

Linux
macOS

for devlopment

Data scheme

yes

scheme-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

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

depending on connected data-source

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

Clojure
Java

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

Lua

user defined functions

yes, depending on connected data-source

Triggers

By using transaction functions

publish/subscribe channels provide some trigger functionality

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

yes

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

Source-replica replication

yes

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

Password-based authentication

Users with fine-grained authorization concept, user roles and pluggable authentication

SQL standard access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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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

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