DBMS > Badger vs. ClickHouse vs. GBase vs. Hyprcubd vs. NuoDB

System Properties Comparison Badger vs. ClickHouse vs. GBase vs. Hyprcubd vs. NuoDB

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Serverless Time Series DBMS

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

github.com/dgraph-io/badger

clickhouse.com

www.gbase.cn

hyprcubd.com (offline)

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

godoc.org/github.com/dgraph-io/badger

clickhouse.com/docs

doc.nuodb.com

Developer

DGraph Labs

Clickhouse Inc.

General Data Technology Co., Ltd.

Hyprcubd, Inc.

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2017

2016

2004

2013

Current release

v24.4.1.2088-stable, May 2024

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

limited edition free

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.

ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

C++

C, Java, Python

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

Standard with numerous extensions

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

ADO.NET
C API
JDBC
ODBC

gRPC (https)

ADO.NET
JDBC
ODBC

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

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

Server-side scripts

Stored procedures

yes

user defined functions

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

horizontal partitioning (by range, list and hash) and vertical partitioning

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

none

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

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

Temporary table

User concepts

Access control

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

yes

token access

Standard SQL roles/ privileges, Administrative Users

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