DBMS > AnzoGraph DB vs. PouchDB vs. Trino vs. XTDB

System Properties Comparison AnzoGraph DB vs. PouchDB vs. Trino vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

JavaScript DBMS with an API inspired by CouchDB

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

A general purpose database with bitemporal SQL and Datalog and graph queries

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	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

cambridgesemantics.com/anzograph

pouchdb.com

trino.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

pouchdb.com/guides

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

www.xtdb.com/docs

Social network pages

Developer

Cambridge Semantics

Apache Software Foundation

Trino Software Foundation

Juxt Ltd.

Initial release

2018

2012

2020 rebranded from PrestoSQL

2019

Current release

2.3, January 2021

7.1.1, June 2019

1.19, September 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

Open Source

MIT License

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

JavaScript

Java

Clojure

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

Linux
macOS

for devlopment

All OS with a Java 8 (and higher) VM
Linux

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

via views

depending on connected data-source

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

HTTP REST

only for PouchDB Server
JavaScript API

JDBC
RESTful HTTP API
Trino CLI

HTTP REST
JDBC

Supported programming languages

C++
Java
Python

JavaScript

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Clojure
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

View functions in JavaScript

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

with a proxy-based framework, named couchdb-lounge

depending on connected data-source

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

depending on connected data-source

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency

depending on connected data-source

Foreign keys

Referential integrity

not needed in graphs

Transaction concepts

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

ACID

depending on connected data-source

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

depending on connected data-source

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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...
» 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

One busy week to go before Trino Fest 2024
6 June 2024

60: Trino calling AI
22 May 2024

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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Recent citations in the news

AnzoGraph review: A graph database for deep analytics
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23 January 2020, Solutions Review

Back to the future: Does graph database success hang on query language?
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