DBMS > Cubrid vs. Dgraph vs. Google Cloud Bigtable vs. GreptimeDB vs. HyperSQL

System Properties Comparison Cubrid vs. Dgraph vs. Google Cloud Bigtable vs. GreptimeDB vs. HyperSQL

Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Distributed and scalable native Graph DBMS

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

Relational DBMS

Graph DBMS

Key-value store
Wide column store

Time Series DBMS

Relational DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph 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	3.49
Rank	#87	Overall
	#47	Relational DBMS

Website

cubrid.com (korean)
cubrid.org (english)

dgraph.io

cloud.google.com/bigtable

greptime.com

hsqldb.org

Technical documentation

cubrid.org/manuals

dgraph.io/docs

cloud.google.com/bigtable/docs

docs.greptime.com

hsqldb.org/web/hsqlDocsFrame.html

Developer

CUBRID Corporation, CUBRID Foundation

Dgraph Labs, Inc.

Google

Greptime Inc.

Initial release

2008

2016

2015

2022

2001

Current release

11.0, January 2021

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

Open Source

based on BSD license

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, C++, Java

Rust

Java

Server operating systems

Linux
Windows

Linux
OS X
Windows

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Data scheme

yes

schema-free

schema-free, schema definition possible

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

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

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

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

gRPC
HTTP API
JDBC

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

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

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

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

C++
Erlang
Go
Java
JavaScript

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Python

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Synchronous replication via Raft

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

none

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

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

fine grained access rights according to SQL-standard

Planned for future releases

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

Simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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

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