DBMS > Databend vs. Google Cloud Bigtable vs. HyperSQL vs. Transbase

System Properties Comparison Databend vs. Google Cloud Bigtable vs. HyperSQL vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Key-value store
Wide column store

Relational DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

cloud.google.com/bigtable

hsqldb.org

www.transaction.de/en/products/transbase.html

Technical documentation

docs.databend.com

cloud.google.com/bigtable/docs

hsqldb.org/web/hsqlDocsFrame.html

www.transaction.de/en/products/transbase/features.html

Developer

Databend Labs

Google

Transaction Software GmbH

Initial release

2021

2015

2001

1987

Current release

1.0.59, April 2023

2.7.2, June 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

based on BSD license

commercial

free development 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

Rust

Java

C and C++

Server operating systems

hosted
Linux
macOS

hosted

All OS with a Java VM

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

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

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

CLI Client
JDBC
RESTful HTTP API

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

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

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

All languages supporting JDBC/ODBC
Java

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

Java, SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

none

Source-replica replication

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

yes

Atomic single-row operations

ACID

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

Users with fine-grained authorization concept, user roles

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

fine grained access rights according to SQL-standard

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