DBMS > FoundationDB vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. Prometheus vs. SAP HANA

System Properties Comparison FoundationDB vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. Prometheus vs. SAP HANA

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

Fully managed big data interactive analytics platform

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Open-source Time Series DBMS and monitoring system

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

column oriented

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

github.com/apple/foundationdb

azure.microsoft.com/services/data-explorer

www.postgres-xl.org

prometheus.io

www.sap.com/products/hana.html

Technical documentation

apple.github.io/foundationdb

docs.microsoft.com/en-us/azure/data-explorer

www.postgres-xl.org/documentation

prometheus.io/docs

help.sap.com/hana

Developer

FoundationDB

Microsoft

SAP

Initial release

2013

2019

2014

since 2012, originally named StormDB

2015

2010

Current release

6.2.28, November 2020

cloud service with continuous releases

10 R1, October 2018

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Mozilla public license

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux
macOS

Linux
Windows

Appliance or cloud-service

Data scheme

schema-free

some layers support schemas

Fixed schema with schema-less datatypes (dynamic)

yes

Typing

predefined data types such as float or date

some layers support typing

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

yes

Numeric data only

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

XML type, but no XML query functionality

Import of XML data possible

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

supported in specific SQL layer only

Kusto Query Language (KQL), SQL subset

yes

distributed, parallel query execution

yes

APIs and other access methods

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

in SQL-layer only

Yes, possible languages: KQL, Python, R

user defined functions

SQLScript, R

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes

by Federation

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

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

ACID

MVCC

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

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

yes

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.