DBMS > GigaSpaces vs. GraphDB vs. Snowflake vs. Sphinx

System Properties Comparison GigaSpaces vs. GraphDB vs. Snowflake vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Cloud-based data warehousing service for structured and semi-structured data

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Graph DBMS
RDF store

Relational DBMS

Search engine

Secondary database models

Graph DBMS
Search engine

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

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	3.10
Rank	#100	Overall
	#7	Graph DBMS
	#4	RDF stores

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

Technical documentation

docs.gigaspaces.com/latest/landing.html

graphdb.ontotext.com/documentation

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

Social network pages

Developer

Gigaspaces Technologies

Ontotext

Snowflake Computing Inc.

Sphinx Technologies Inc.

Initial release

2000

2014

2001

Current release

15.5, September 2020

10.4, October 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

Some plugins of GraphDB Workbench are open sourced

commercial

Open Source

GPL version 2, commercial licence 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++, .Net

Java

C++

Server operating systems

Linux
macOS
Solaris
Windows

All OS with a Java VM
Linux
OS X
Windows

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

schema-free and OWL/RDFS-schema support; RDF shapes

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-99 for query and DML statements

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

yes

SQL-like query language (SphinxQL)

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

CLI Client
JDBC
ODBC

Proprietary protocol

Supported programming languages

.Net
C++
Java
Python
Scala

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

well-defined plugin interfaces; JavaScript server-side extensibility

user defined functions

Triggers

yes, event driven architecture

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Immediate Consistency

Foreign keys

Referential integrity

yes

Constraint checking

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

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes

User concepts

Access control

Role-based access control

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

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

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

How Knowledge Graphs Power Data Mesh and Data Fabric
10 April 2024

Building Smarter Financial Services: The Role of Semantic Technologies, Knowledge Graphs and Generative AI
3 April 2024

Using GraphDB’s Natural Language Interface to Talk with Your Content
29 March 2024

Choosing A Graph Data Model to Best Serve Your Use Case
27 March 2024

Event Extraction Based on Fine-Tuned Text2Event Transformer Speeds up the Fact-checking Process
22 March 2024

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