DBMS > Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. GreptimeDB vs. RocksDB

System Properties Comparison Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. GreptimeDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Graph DBMS

Relational DBMS

Key-value store
Wide column store

Time Series DBMS

Key-value store

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

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

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

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

Website

dgraph.io

www.esgyn.cn

cloud.google.com/bigtable

greptime.com

rocksdb.org

Technical documentation

dgraph.io/docs

cloud.google.com/bigtable/docs

docs.greptime.com

github.com/facebook/rocksdb/wiki

Developer

Dgraph Labs, Inc.

Esgyn

Google

Greptime Inc.

Facebook, Inc.

Initial release

2016

2015

2022

2013

Current release

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

Open Source

BSD

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

C++, Java

Rust

C++

Server operating systems

Linux
OS X
Windows

Linux

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux

Data scheme

schema-free

yes

schema-free

schema-free, schema definition possible

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

APIs and other access methods

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

ADO.NET
JDBC
ODBC

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

gRPC
HTTP API
JDBC

C++ API
Java API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

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

C++
Erlang
Go
Java
JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication between multi datacenters

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

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

yes

Concurrency

Support for concurrent manipulation of data

yes

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

fine grained access rights according to SQL-standard

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

Simple rights management via user accounts

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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