DBMS > Dgraph vs. EventStoreDB vs. Google Cloud Bigtable vs. H2 vs. YottaDB

System Properties Comparison Dgraph vs. EventStoreDB vs. Google Cloud Bigtable vs. H2 vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A fast and solid embedded Key-value store

Primary database model

Graph DBMS

Event Store

Key-value store
Wide column store

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

Relational DBMS

using the Octo plugin

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

dgraph.io

www.eventstore.com

cloud.google.com/bigtable

www.h2database.com

yottadb.com

Technical documentation

dgraph.io/docs

developers.eventstore.com

cloud.google.com/bigtable/docs

www.h2database.com/html/main.html

yottadb.com/resources/documentation

Developer

Dgraph Labs, Inc.

Event Store Limited

Google

Thomas Mueller

YottaDB, LLC

Initial release

2016

2012

2015

2005

2001

Current release

21.2, February 2021

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
OS X
Windows

Linux
Windows

hosted

All OS with a Java VM

Docker
Linux

Data scheme

schema-free

yes

schema-free

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

SQL

Support of SQL

yes

by using the Octo plugin

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
ODBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
Python

Java

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Internal replication in Colossus, and regional replication between two clusters in different zones

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

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

Planned for future releases

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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More resources

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