DBMS > OrientDB vs. RocksDB vs. Trino vs. Vitess

System Properties Comparison OrientDB vs. RocksDB vs. Trino vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

Multi-model DBMS (Document, Graph, Key/Value)

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

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Document store
Graph DBMS
Key-value store

Key-value store

Relational DBMS

Secondary database models

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

Document store
Spatial DBMS

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

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

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

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

Technical documentation

www.orientdb.com/docs/last/index.html

github.com/facebook/rocksdb/wiki

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

vitess.io/docs

Social network pages

Developer

OrientDB LTD; CallidusCloud; SAP

Facebook, Inc.

Trino Software Foundation

The Linux Foundation, PlanetScale

Initial release

2010

2013

2012

2020 rebranded from PrestoSQL

2013

Current release

3.2.29, March 2024

8.11.4, April 2024

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

BSD

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

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

C++

Java

Server operating systems

All OS with a Java JDK (>= JDK 6)

Linux

Linux
macOS

for devlopment

Docker
Linux
macOS

Data scheme

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

Secondary indexes

yes

depending on connected data-source

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

with proprietary extensions

APIs and other access methods

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

C++ API
Java API

JDBC
RESTful HTTP API
Trino CLI

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java, Javascript

yes, depending on connected data-source

yes

proprietary syntax

Triggers

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

depending on connected data-source

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

depending on connected data-source

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

depending on connected data-source

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

relationship in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

yes

depending on connected data-source

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

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

User concepts

Access control

Access rights for users and roles; record level security configurable

SQL standard access control

Users with fine-grained authorization concept

no user groups or roles

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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