DBMS > Firebolt vs. Google BigQuery vs. LokiJS vs. Microsoft Azure Synapse Analytics vs. OpenQM

System Properties Comparison Firebolt vs. Google BigQuery vs. LokiJS vs. Microsoft Azure Synapse Analytics vs. OpenQM

Editorial information provided by DB-Engines

Name

Description

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Large scale data warehouse service with append-only tables

In-memory JavaScript DBMS

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

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

Score	1.49
Rank	#148	Overall
	#68	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	0.44
Rank	#256	Overall
	#40	Document stores

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Website

www.firebolt.io

cloud.google.com/bigquery

github.com/techfort/LokiJS

azure.microsoft.com/services/synapse-analytics

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

docs.firebolt.io

cloud.google.com/bigquery/docs

techfort.github.io/LokiJS

docs.microsoft.com/azure/synapse-analytics

Developer

Firebolt Analytics Inc.

Google

Microsoft

Rocket Software, originally Martin Phillips

Initial release

2020

2010

2014

2016

1993

Current release

3.4-12

License

Commercial or Open Source

commercial

Open Source

commercial

Open Source

GPLv2, extended commercial license 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.

Implementation language

JavaScript

C++

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-free

yes

with some exceptions

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

.Net
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

JavaScript API

ADO.NET
JDBC
ODBC

Supported programming languages

Go
JavaScript (Node.js)
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

C#
Java
PHP

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

View functions in JavaScript

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

Since BigQuery is designed for querying data

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

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

Google Cloud Identity & Access Management (IAM)

yes

Access rights can be defined down to the item level

More information provided by the system vendor

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.