DBMS > Badger vs. Brytlyt vs. DataFS vs. Google Cloud Spanner

System Properties Comparison Badger vs. Brytlyt vs. DataFS vs. Google Cloud Spanner

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Editorial information provided by DB-Engines

Name

Description

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

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Primary database model

Secondary database models

Graph DBMS

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

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	0.27
Rank	#292	Overall
	#132	Relational DBMS

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Website

github.com/dgraph-io/badger

brytlyt.io

newdatabase.com

cloud.google.com/spanner

Technical documentation

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

docs.brytlyt.io

dev.mobiland.com/Overview.xsp

cloud.google.com/spanner/docs

Developer

DGraph Labs

Brytlyt

Mobiland AG

Google

Initial release

2017

2016

2018

2017

Current release

5.0, August 2023

1.1.263, October 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

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++ and CUDA

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Windows

hosted

Data scheme

schema-free

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

Query statements complying to ANSI 2011

APIs and other access methods

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

.NET Client API
Proprietary client DLL
WinRT client

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C
C#
C++
VB.Net

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Triggers

yes

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

none

Proprietary Sharding system

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication with 3 replicas for regional instances.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

ACID

Strict serializable isolation

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Windows-Profile

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

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More resources

Recent citations in the news

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

provided by Google 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

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

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21 May 2020, AiThority

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Google Cloud Enhances Spanner with Dual-Region Configuration
1 August 2024, InfoQ.com

New features make Google's Spanner a database for AI
1 August 2024, TechTarget

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1 August 2024, TechCrunch

provided by Google News

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