DBMS > Brytlyt vs. Databend vs. Datastax Enterprise vs. Google Cloud Firestore

System Properties Comparison Brytlyt vs. Databend vs. Datastax Enterprise vs. Google Cloud Firestore

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

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

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Primary database model

Relational DBMS

Wide column store

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	0.27
Rank	#289	Overall
	#131	Relational DBMS

Score	0.26
Rank	#291	Overall
	#132	Relational DBMS

Score	4.74
Rank	#66	Overall
	#4	Wide column stores

Score	6.46
Rank	#54	Overall
	#9	Document stores

Website

brytlyt.io

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

www.datastax.com/products/datastax-enterprise

firebase.google.com/products/firestore

Technical documentation

docs.brytlyt.io

docs.databend.com

docs.datastax.com

firebase.google.com/docs/firestore

Developer

Brytlyt

Databend Labs

DataStax

Google

Initial release

2016

2021

2011

2017

Current release

5.0, August 2023

1.0.59, April 2023

6.8, April 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 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.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Implementation language

C, C++ and CUDA

Rust

Java

Server operating systems

Linux
OS X
Windows

hosted
Linux
macOS

Linux
OS X

hosted

Data scheme

yes

schema-free

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

SQL-like DML and DDL statements (CQL); Spark SQL

APIs and other access methods

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

CLI Client
JDBC
RESTful HTTP API

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Go
Java
JavaScript (Node.js)
Python
Rust

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

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes, Firebase Rules & Cloud Functions

Triggers

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

configurable replication factor, datacenter aware, advanced replication for edge computing

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Atomicity and isolation are supported for single operations

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles

Access rights for users can be defined per object

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more

Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
» more

Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
» more

Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more

Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more

Licensing and pricing models

Annual subscription
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

show all

Recent citations in the news

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

About Charlie McIver
27 October 2022, Fintech Finance

provided by Google News

Apache Iceberg Rust Released
9 September 2024, iProgrammer

provided by Google News

DataStax Announces Vector Search for DataStax Enterprise: Bringing the Power of Generative AI to Any Cloud, Hybrid, and On-premises Environments
8 August 2023, Business Wire

DataStax review: Cassandra made faster and easier
20 August 2018, InfoWorld

US Bank is using DataStax Enterprise to overcome legacy and become customer focused
23 May 2019, diginomica

DataStax Luna: Subscription-Based Support for Open-Source Apache Cassandra
20 September 2021, ibm.com

NetApp stacks DataStax onto its Astra Kubernetes storage
20 May 2021, Blocks & Files

provided by Google News

Google launches Firebase Genkit, a new open source framework for building AI-powered apps
14 May 2024, TechCrunch

NoSQL on the Cloud With Python
7 August 2020, Towards Data Science

Google Reveals Android Performance Tuner, Android GPU Inspector and Cloud Firestore
23 March 2020, Wccftech

Spring Boot Tutorial: Building Microservices Deployed to Google Cloud
26 March 2020, InfoQ.com

Google updates Firebase with new emulator and data analysis tools
27 October 2020, VentureBeat

provided by Google News

Share this page