DBMS > Firebolt vs. Hive vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. OpenEdge

System Properties Comparison Firebolt vs. Hive vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. OpenEdge

Editorial information provided by DB-Engines

Name

Description

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

Microsofts flagship relational DBMS

Application development environment with integrated database management system

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.73
Rank	#140	Overall
	#63	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Website

www.firebolt.io

hive.apache.org

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

www.microsoft.com/en-us/sql-server

www.progress.com/openedge

Technical documentation

docs.firebolt.io

cwiki.apache.org/confluence/display/Hive/Home

learn.microsoft.com/en-US/sql/sql-server

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Firebolt Analytics Inc.

Apache Software Foundation

initially developed by Facebook

Microsoft

Progress Software Corporation

Initial release

2020

2012

1989

1984

Current release

3.1.3, April 2022

SQL Server 2022, November 2022

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

restricted free version is 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.

SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.

Implementation language

Java

C++

Server operating systems

hosted

All OS with a Java VM

hosted

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

close to SQL 92

APIs and other access methods

.Net
ODBC
RESTful HTTP API

JDBC
ODBC
Thrift

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC

Supported programming languages

Go
JavaScript (Node.js)
Python

C++
Java
PHP
Python

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

selectable replication factor

yes

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

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

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

User concepts

Access control

Access rights for users, groups and roles

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

Users and groups

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.