DBMS > Brytlyt vs. Cubrid vs. Google BigQuery vs. Newts vs. SingleStore

System Properties Comparison Brytlyt vs. Cubrid vs. Google BigQuery vs. Newts vs. SingleStore

Editorial information provided by DB-Engines

Name

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

Large scale data warehouse service with append-only tables

Time Series DBMS based on Cassandra

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Website

brytlyt.io

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

cloud.google.com/bigquery

opennms.github.io/newts

www.singlestore.com

Technical documentation

docs.brytlyt.io

cubrid.org/manuals

cloud.google.com/bigquery/docs

github.com/OpenNMS/newts/wiki

docs.singlestore.com

Developer

Brytlyt

CUBRID Corporation, CUBRID Foundation

Google

OpenNMS Group

SingleStore Inc.

Initial release

2016

2008

2010

2014

2013

Current release

5.0, August 2023

11.0, January 2021

8.5, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

commercial

free developer edition available

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C, C++ and CUDA

C, C++, Java

Java

C++, Go

Server operating systems

Linux
OS X
Windows

Linux
Windows

hosted

Linux
OS X
Windows

Linux

64 bit version required

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

but no triggers and foreign keys

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP/JSON API

HTTP REST
Java API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Java Stored Procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Fine grained access control via users, groups and roles

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

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
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