DBMS > Brytlyt vs. CouchDB vs. GridDB vs. Splice Machine

System Properties Comparison Brytlyt vs. CouchDB vs. GridDB vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

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

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Scalable in-memory time series database optimized for IoT and Big Data

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

Key-value store
Relational DBMS

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

Score	0.27
Rank	#292	Overall
	#132	Relational DBMS

Score	7.46
Rank	#51	Overall
	#7	Document stores

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Website

Technical documentation

docs.brytlyt.io

docs.couchdb.org/en/stable

docs.griddb.net

splicemachine.com/how-it-works

Developer

Brytlyt

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Toshiba Corporation

Splice Machine

Initial release

2016

2005

2013

2014

Current release

5.0, August 2023

3.3.3, December 2023

5.1, August 2022

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++ and CUDA

Erlang

C++

Java

Server operating systems

Linux
OS X
Windows

Android
BSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

via views

yes

SQL

Support of SQL

yes

SQL92, SQL-like TQL (Toshiba Query Language)

yes

APIs and other access methods

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

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

View functions in JavaScript

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single document possible

ACID at container level

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

yes, multi-version concurrency control (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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

Access rights for users, groups and roles according to SQL-standard

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More resources

DB-Engines blog posts

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Recent citations in the news

Opensignal Announces Acquisition of Brytlyt GPU-based Data Analytics & Visualization Technology
5 June 2024, PR Web

Brytlyt releases version 5.0, introducing a more intuitive, intelligent and flexible analytics platform
1 August 2023, PR Newswire

Bringing GPUs To Bear On Bog Standard Relational Databases
26 February 2018, The Next Platform

London’s Brytlyt raises €4.4 million for its data analytics and visualisation technology
22 December 2021, EU-Startups

Brytlyt Unleashes Serverless GPU-Acceleration for Analytics
15 September 2021, PR Newswire

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19 January 2021, PR Newswire

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