DBMS > AllegroGraph vs. Hypertable vs. Microsoft SQL Server vs. Oracle NoSQL vs. QuestDB

System Properties Comparison AllegroGraph vs. Hypertable vs. Microsoft SQL Server vs. Oracle NoSQL vs. QuestDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

High performance, persistent RDF store with additional support for Graph DBMS

An open source BigTable implementation based on distributed file systems such as Hadoop

Microsofts flagship relational DBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A high performance open source SQL database for time series data

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Wide column store

Relational DBMS

Document store
Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Website

allegrograph.com

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

www.oracle.com/database/nosql/technologies/nosql

questdb.io

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

questdb.io/docs

Developer

Franz Inc.

Hypertable Inc.

Microsoft

Oracle

QuestDB Technology Inc

Initial release

2004

2009

1989

2011

2014

Current release

8.0, December 2023

0.9.8.11, March 2016

SQL Server 2022, November 2022

23.3, December 2023

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

GNU version 3. Commercial license available

commercial

restricted free version is available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Apache 2.0

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++

Java

Java (Zero-GC), C++, Rust

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Windows

Linux
Solaris SPARC/x86

Linux
macOS
Windows

Data scheme

yes

RDF schemas

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

schema-free via InfluxDB Line Protocol

Typing

predefined data types such as float or date

yes

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.

bulk load of XML files possible

yes

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SPARQL is used as query language

yes

SQL-like DML and DDL statements

SQL with time-series extensions

APIs and other access methods

RESTful HTTP API
SPARQL

C++ API
Thrift

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

RESTful HTTP API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C++
Java
Perl
PHP
Python
Ruby

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

C
C#
Go
Java
JavaScript (Node.js)
Python

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

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

Sharding

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor on file system level

yes, but depending on the SQL-Server Edition

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

ACID for single-table writes

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

off heap cache

yes

through memory mapped files

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

News

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

QuestDB and Raspberry Pi 5 benchmark, a pocket-sized powerhouse
8 May 2024

Build your own resource monitor with QuestDB and Grafana
6 May 2024

Does "vpmovzxbd" Scare You? Here's Why it Doesn't Have To
12 April 2024

Create an ADS-B flight radar with QuestDB and a Raspberry Pi
8 April 2024

Build a temperature IoT sensor with Raspberry Pi Pico & QuestDB
5 April 2024

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.