DBMS > EventStoreDB vs. RocksDB vs. SwayDB vs. TimescaleDB vs. Trino

System Properties Comparison EventStoreDB vs. RocksDB vs. SwayDB vs. TimescaleDB vs. Trino

Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

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

Primary database model

Secondary database models

Relational 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	1.10
Rank	#179	Overall
	#1	Event Stores

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

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

Technical documentation

developers.eventstore.com

github.com/facebook/rocksdb/wiki

docs.timescale.com

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

Social network pages

Developer

Event Store Limited

Facebook, Inc.

Simer Plaha

Timescale

Trino Software Foundation

Initial release

2012

2013

2018

2017

2012

2020 rebranded from PrestoSQL

Current release

21.2, February 2021

8.11.4, April 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

BSD

Open Source

GNU Affero GPL V3.0

Open Source

Apache 2.0

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

C++

Scala

Java

Server operating systems

Linux
Windows

Linux

Linux
OS X
Windows

Linux
macOS

for devlopment

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

full PostgreSQL SQL syntax

yes

APIs and other access methods

C++ API
Java API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

Java
Kotlin
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

yes, across time and space (hash partitioning) attributes

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication with hot standby and reads on replicas

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

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Atomic execution of operations

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.

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...
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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

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8 May 2024

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24 April 2024

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15 April 2024

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58: Understanding your users with Trino and Mitzu
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.