DBMS > Firebolt vs. H2 vs. Microsoft Azure Table Storage vs. RavenDB vs. Snowflake

System Properties Comparison Firebolt vs. H2 vs. Microsoft Azure Table Storage vs. RavenDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A Wide Column Store for rapid development using massive semi-structured datasets

Open Source Operational and Transactional Enterprise NoSQL Document Database

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.90
Rank	#134	Overall
	#62	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.firebolt.io

www.h2database.com

azure.microsoft.com/en-us/services/storage/tables

ravendb.net

www.snowflake.com

Technical documentation

docs.firebolt.io

www.h2database.com/html/main.html

ravendb.net/docs

docs.snowflake.net/manuals/index.html

Developer

Firebolt Analytics Inc.

Thomas Mueller

Microsoft

Hibernating Rhinos

Snowflake Computing Inc.

Initial release

2020

2005

2012

2010

2014

Current release

2.2.220, July 2023

5.4, July 2022

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

AGPL version 3, commercial license available

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

Java

Server operating systems

hosted

All OS with a Java VM

hosted

Linux
macOS
Raspberry Pi
Windows

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

SQL

Support of SQL

yes

SQL-like query language (RQL)

yes

APIs and other access methods

.Net
ODBC
RESTful HTTP API

JDBC
ODBC

RESTful HTTP API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

Go
JavaScript (Node.js)
Python

Java

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

Access rights based on private key authentication or shared access signatures

Authorization levels configured per client per database

Users with fine-grained authorization concept, user roles and pluggable authentication

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