DBMS > eXtremeDB vs. GraphDB vs. Memcached vs. Snowflake vs. SQream DB

System Properties Comparison eXtremeDB vs. GraphDB vs. Memcached vs. Snowflake vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

Natively in-memory DBMS with options for persistency, high-availability and clustering

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.

In-memory key-value store, originally intended for caching

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS
Time Series DBMS

Graph DBMS
RDF store

Key-value store

Relational DBMS

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

Score	0.79
Rank	#212	Overall
	#100	Relational DBMS
	#18	Time Series DBMS

Score	2.76
Rank	#99	Overall
	#8	Graph DBMS
	#4	RDF stores

Score	16.84
Rank	#32	Overall
	#4	Key-value stores

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.62
Rank	#234	Overall
	#109	Relational DBMS

Website

Technical documentation

www.mcobject.com/docs/extremedb.htm

graphdb.ontotext.com/documentation

github.com/memcached/memcached/wiki

docs.snowflake.net/manuals/index.html

docs.sqream.com

Social network pages

Developer

McObject

Ontotext

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Snowflake Computing Inc.

SQream Technologies

Initial release

2001

2000

2003

2014

2017

Current release

8.2, 2021

10.4, October 2023

1.6.29, June 2024

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

BSD license

commercial

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

C and C++

Java

C++, CUDA, Haskell, Java, Scala

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

All OS with a Java VM
Linux
OS X
Windows

FreeBSD
Linux
OS X
Unix
Windows

hosted

Linux

Data scheme

yes

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

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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.

support of XML interfaces available

yes

Secondary indexes

yes

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

SQL

Support of SQL

yes

with the option: eXtremeSQL

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

yes

APIs and other access methods

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

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

Proprietary protocol

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

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

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

well-defined plugin interfaces; JavaScript server-side extensibility

user defined functions

user defined functions in Python

Triggers

yes

by defining events

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

none

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Multi-source replication

none

Repcached, a Memcached patch, provides this functionallity

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Optimistic (MVCC) and pessimistic (locking) strategies available

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

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.

yes

using SASL (Simple Authentication and Security Layer) protocol

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

GraphDB in Action: Using Semantics To Push The Envelope Of Software Engineering, Machine Learning, and E-Health Domains
11 September 2024

Accelerating End-to-end Knowledge Graph Solutions with Ontotext’s LinkedLifeData Inventory: The Case of Target Discovery
30 August 2024

Using Entity Linking to Turn Your Graph into a Knowledge Graph
23 August 2024

Considerations to Creating a Graph Center of Excellence: 5 Elements to Ensure Success
22 August 2024

The Power of Knowledge Graphs – A Chat with Perfect Memory and Ontotext
16 August 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.