DBMS > AgensGraph vs. IBM Db2 Event Store vs. Snowflake vs. Trino

System Properties Comparison AgensGraph vs. IBM Db2 Event Store vs. Snowflake vs. Trino

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Distributed Event Store optimized for Internet of Things use cases

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

Graph DBMS
Relational DBMS

Event Store
Time Series DBMS

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	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Website

bitnine.net/agensgraph

www.ibm.com/products/db2-event-store

www.snowflake.com

trino.io

Technical documentation

bitnine.net/documentation

www.ibm.com/docs/en/db2-event-store

docs.snowflake.net/manuals/index.html

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

Social network pages

Developer

Bitnine Global Inc.

IBM

Snowflake Computing Inc.

Trino Software Foundation

Initial release

2016

2017

2014

2012

2020 rebranded from PrestoSQL

Current release

2.1, December 2018

2.0

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free developer edition available

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C and C++

Java

Server operating systems

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

hosted

Linux
macOS

for devlopment

Data scheme

depending on used data model

yes

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

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.

yes

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

APIs and other access methods

Cypher Query Language
JDBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

C
Java
JavaScript
Python

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

yes, depending on connected data-source

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

yes

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Active-active shard 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

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

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

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Licensing and pricing models

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