DBMS > AnzoGraph DB vs. Apache Drill vs. Hawkular Metrics vs. Microsoft SQL Server vs. Prometheus

System Properties Comparison AnzoGraph DB vs. Apache Drill vs. Hawkular Metrics vs. Microsoft SQL Server vs. Prometheus

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

Microsofts flagship relational DBMS

Open-source Time Series DBMS and monitoring system

Primary database model

Graph DBMS
RDF store

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Website

cambridgesemantics.com/anzograph

drill.apache.org

www.hawkular.org

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

prometheus.io

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

drill.apache.org/docs

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

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

prometheus.io/docs

Developer

Cambridge Semantics

Apache Software Foundation

Community supported by Red Hat

Microsoft

Initial release

2018

2012

2014

1989

2015

Current release

2.3, January 2021

1.20.3, January 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux

Linux
OS X
Windows

Linux
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
ODBC
RESTful HTTP API

HTTP REST

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

RESTful HTTP/JSON API

Supported programming languages

C++
Java
Python

C++

Go
Java
Python
Ruby

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

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

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

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

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

based on Cassandra

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication factor

based on Cassandra

yes, but depending on the SQL-Server Edition

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

none

Foreign keys

Referential integrity

not needed in graphs

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

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Depending on the underlying data source

yes

User concepts

Access control

Access rights for users and roles

Depending on the underlying data source

fine grained access rights according to SQL-standard

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