DBMS > Apache Impala vs. Firebird vs. Microsoft SQL Server vs. OushuDB vs. Rockset

System Properties Comparison Apache Impala vs. Firebird vs. Microsoft SQL Server vs. OushuDB vs. Rockset

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Firebird is an open source RDBMS forked from Borland's InterBase

Microsofts flagship relational DBMS

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

Document store

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	19.46
Rank	#30	Overall
	#18	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Score	1.07
Rank	#180	Overall
	#31	Document stores

Website

impala.apache.org

www.firebirdsql.org

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

www.oushu.com/product/oushuDB

rockset.com

Technical documentation

impala.apache.org/impala-docs.html

www.firebirdsql.org/en/reference-manuals

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

www.oushu.com/documentation

docs.rockset.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Firebird Foundation

Microsoft

Oushu

Rockset

Initial release

2013

2000

As fork of Borland's InterBase

1989

2019

Current release

4.1.0, June 2022

5.0.1, August 2024

SQL Server 2022, November 2022

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Initial Developer's Public License

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

C++

C and C++

C++

Server operating systems

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
Windows

Linux

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like DML and DDL statements

yes

Full-featured ANSI SQL support

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
ODBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

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

JDBC
ODBC

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

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

C
C++

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PSQL

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

none

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

yes

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

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

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

Kerberos, SSL and role based access

Access rights for users and organizations can be defined via Rockset console

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.