DBMS > EventStoreDB vs. JanusGraph vs. SAP HANA vs. Trino

System Properties Comparison EventStoreDB vs. JanusGraph vs. SAP HANA vs. Trino

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Editorial information provided by DB-Engines

Name

Description

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

In-memory, column based data store. Available as appliance or cloud service

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

Primary database model

Event Store

Graph DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial 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	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

www.eventstore.com

janusgraph.org

www.sap.com/products/hana.html

trino.io

Technical documentation

developers.eventstore.com

docs.janusgraph.org

help.sap.com/hana

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

Social network pages

Developer

Event Store Limited

Linux Foundation; originally developed as Titan by Aurelius

SAP

Trino Software Foundation

Initial release

2012

2017

2010

2012

2020 rebranded from PrestoSQL

Current release

21.2, February 2021

0.6.3, February 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

also available as a cloud based 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

Java

Server operating systems

Linux
Windows

Linux
OS X
Unix
Windows

Appliance or cloud-service

Linux
macOS

for devlopment

Data scheme

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

SQL

Support of SQL

yes

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

Clojure
Java
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

SQLScript, R

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

yes

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

yes

SQL standard access control

More information provided by the system vendor

Specific characteristics

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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

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