DBMS > Hive vs. Microsoft Azure Data Explorer vs. Prometheus vs. SAP Advantage Database Server

System Properties Comparison Hive vs. Microsoft Azure Data Explorer vs. Prometheus vs. SAP Advantage Database Server

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Editorial information provided by DB-Engines

Name

Description

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

Fully managed big data interactive analytics platform

Open-source TimeSeries DBMS and monitoring system

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Relational DBMS

column oriented

Time Series DBMS

Relational DBMS

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)
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

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

Score	79.48
Rank	#17	Overall
	#11	Relational DBMS

Score	7.08
Rank	#61	Overall
	#34	Relational DBMS

Score	6.69
Rank	#63	Overall
	#3	Time Series DBMS

Score	3.59
Rank	#92	Overall
	#48	Relational DBMS

Website

hive.apache.org

azure.microsoft.com/services/data-explorer

prometheus.io

www.sap.com/products/advantage-database-server.html

Technical documentation

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

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

prometheus.io/docs

Developer

Apache Software Foundation

initially developed by Facebook

Microsoft

Sybase, SAP

Initial release

2012

2019

2015

1993

Current release

3.1.2, August 2019

cloud service with continuous releases

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

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.

Implementation language

Java

Server operating systems

All OS with a Java VM

hosted

Linux
Windows

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

yes

Typing

predefined data types such as float or date

yes

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

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

Import of XML data possible

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

JDBC
ODBC
Thrift

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

RESTful HTTP/JSON API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C++
Java
PHP
Python

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

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

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Yes, possible languages: KQL, Python, R

yes

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

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

yes

by Federation

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
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

Eventual Consistency
Immediate Consistency

none

Immediate 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

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.

caching of (temporary) tables can be configured

User concepts

Access control

Access rights for users, groups and roles

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Azure Data Explorer is a fast and highly scalable data exploration service for log...
» more

Competitive advantages

Kusto Query Language (innovative query language, optimized for high performance data...
» more

Typical application scenarios

IoT applications IoT devices generate billions of sensor readings. Normalizing and...
» more

Key customers

Microsoft, DocuSign, Taboola, Bosch, Siemens Healthineers, Bühler, Ecolab, Zoomd
» more

Market metrics

Azure Data Explorer is the data service for Azure Monitor, Azure Time Series Insights,...
» more

Licensing and pricing models

An Azure Data Explorer cluster is a pair of engine and data management clusters which...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.