DBMS > Apache Impala vs. EsgynDB vs. FoundationDB vs. jBASE vs. Microsoft SQL Server

System Properties Comparison Apache Impala vs. EsgynDB vs. FoundationDB vs. jBASE vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

Analytic DBMS for Hadoop

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Ordered key-value store. Core features are complimented by layers.

A robust multi-value DBMS comprising development tools and middleware

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Multivalue DBMS

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	1.07
Rank	#188	Overall
	#31	Document stores
	#28	Key-value stores
	#86	Relational DBMS

Score	1.43
Rank	#160	Overall
	#3	Multivalue DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Website

impala.apache.org

www.esgyn.cn

github.com/apple/foundationdb

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

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

Technical documentation

impala.apache.org/impala-docs.html

apple.github.io/foundationdb

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Esgyn

FoundationDB

Rocket Software (formerly Zumasys)

Microsoft

Initial release

2013

2015

2013

1991

1989

Current release

4.1.0, June 2022

6.2.28, November 2020

5.7

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C++, Java

C++

Server operating systems

Linux

Linux
OS X
Windows

AIX
Linux
Windows

Linux
Windows

Data scheme

yes

schema-free

some layers support schemas

schema-free

yes

Typing

predefined data types such as float or date

yes

some layers support typing

optional

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

supported in specific SQL layer only

Embedded SQL for jBASE in BASIC

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

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

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
Basic
Jabbascript
Java

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

in SQL-layer only

yes

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication between multi datacenters

yes

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

in SQL-layer only

yes

Transaction concepts

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

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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