DBMS > Hawkular Metrics vs. Microsoft Azure Data Explorer vs. NuoDB vs. Oracle vs. Oracle Berkeley DB

System Properties Comparison Hawkular Metrics vs. Microsoft Azure Data Explorer vs. NuoDB vs. Oracle vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

Description

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Fully managed big data interactive analytics platform

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Widely used RDBMS

Widely used in-process key-value store

Primary database model

column oriented

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

www.hawkular.org

azure.microsoft.com/services/data-explorer

www.3ds.com/nuodb-distributed-sql-database

www.oracle.com/database

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

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

doc.nuodb.com

docs.oracle.com/en/database

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Community supported by Red Hat

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2014

2019

2013

1980

1994

Current release

cloud service with continuous releases

23c, September 2023

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

limited edition free

commercial

restricted free version is available

Open Source

commercial license available

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

C++

C and C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux
OS X
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

yes

Schemaless in JSON and XML columns

schema-free

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

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

only with the Berkeley DB XML edition

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

yes

with proprietary extensions

yes

SQL interfaced based on SQLite is available

APIs and other access methods

HTTP REST

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

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
Python
Ruby

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

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

Java, SQL

PL/SQL

also stored procedures in Java possible

Triggers

yes

via Hawkular Alerting

yes

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

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

data is dynamically stored/cached on the nodes where it is read/written

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

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

yes

Managed transparently by NuoDB

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Azure Active Directory Authentication

Standard SQL roles/ privileges, Administrative Users

fine grained access rights according to SQL-standard

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