DBMS > AllegroGraph vs. Google Cloud Spanner vs. Graphite vs. Hyprcubd vs. SAP HANA

System Properties Comparison AllegroGraph vs. Google Cloud Spanner vs. Graphite vs. Hyprcubd vs. SAP HANA

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Serverless Time Series DBMS

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

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

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	1.13
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#9	Vector DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

allegrograph.com

cloud.google.com/spanner

github.com/graphite-project/graphite-web

hyprcubd.com (offline)

www.sap.com/products/hana.html

Technical documentation

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

cloud.google.com/spanner/docs

graphite.readthedocs.io

help.sap.com/hana

Developer

Franz Inc.

Google

Chris Davis

Hyprcubd, Inc.

SAP

Initial release

2004

2017

2006

2010

Current release

8.0, December 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Limited community edition free

commercial

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

Python

Server operating systems

Linux
OS X
Windows

hosted

Linux
Unix

hosted

Appliance or cloud-service

Data scheme

yes

RDF schemas

yes

Typing

predefined data types such as float or date

yes

Numeric data only

yes

time, int, uint, float, string

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

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

Query statements complying to ANSI 2011

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API
SPARQL

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP API
Sockets

gRPC (https)

JDBC
ODBC

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication with 3 replicas for regional instances.

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

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

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

token access

yes

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

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

News

How a Neuro-Symbolic AI Approach Can Improve Trust in AI Apps
23 May 2024

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

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.