DBMS > Brytlyt vs. Google BigQuery vs. HEAVY.AI vs. Microsoft Azure AI Search vs. Realm

System Properties Comparison Brytlyt vs. Google BigQuery vs. HEAVY.AI vs. Microsoft Azure AI Search vs. Realm

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Search-as-a-service for web and mobile app development

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Relational DBMS

Search engine

Document store

Secondary database models

Spatial 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	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

brytlyt.io

cloud.google.com/bigquery

github.com/heavyai/heavydb
www.heavy.ai

azure.microsoft.com/en-us/services/search

realm.io

Technical documentation

docs.brytlyt.io

cloud.google.com/bigquery/docs

docs.heavy.ai

learn.microsoft.com/en-us/azure/search

realm.io/docs

Developer

Brytlyt

Google

HEAVY.AI, Inc.

Microsoft

Realm, acquired by MongoDB in May 2019

Initial release

2016

2010

2016

2015

2014

Current release

5.0, August 2023

5.10, January 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

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

C++ and CUDA

Server operating systems

Linux
OS X
Windows

hosted

Linux

hosted

Android
Backend: server-less
iOS
Windows

Data scheme

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

APIs and other access methods

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

RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

C#
Java
JavaScript
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

user defined functions

in JavaScript

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

In-Memory realm

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 rights according to SQL-standard

yes

using Azure authentication

yes

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