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

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

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Name

Description

Analytic DBMS for Hadoop

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

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

Document store
Graph DBMS
Spatial DBMS

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Trend Chart

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.73
Rank	#140	Overall
	#63	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

impala.apache.org

www.firebolt.io

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

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

www.progress.com/openedge

Technical documentation

impala.apache.org/impala-docs.html

docs.firebolt.io

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

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Firebolt Analytics Inc.

Microsoft

Progress Software Corporation

Initial release

2013

2020

2012

1989

1984

Current release

4.1.0, June 2022

SQL Server 2022, November 2022

OpenEdge 12.2, March 2020

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Server operating systems

Linux

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

SQL-like DML and DDL statements

yes

close to SQL 92

APIs and other access methods

JDBC
ODBC

.Net
ODBC
RESTful HTTP API

RESTful HTTP API

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

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Go
JavaScript (Node.js)
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

selectable replication factor

depending on storage layer

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

based on Apache Sentry and Kerberos

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

Users and groups

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