DBMS > Apache Impala vs. Blazegraph vs. Datastax Enterprise vs. GraphDB vs. Microsoft Azure Cosmos DB

System Properties Comparison Apache Impala vs. Blazegraph vs. Datastax Enterprise vs. GraphDB vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

Analytic DBMS for Hadoop

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

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.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	3.32
Rank	#91	Overall
	#6	Graph DBMS
	#4	RDF stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

impala.apache.org

blazegraph.com

www.datastax.com/products/datastax-enterprise

www.ontotext.com

azure.microsoft.com/services/cosmos-db

Technical documentation

impala.apache.org/impala-docs.html

wiki.blazegraph.com

docs.datastax.com

graphdb.ontotext.com/documentation

learn.microsoft.com/azure/cosmos-db

Social network pages

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Blazegraph

DataStax

Ontotext

Microsoft

Initial release

2013

2006

2011

2000

2014

Current release

4.1.0, June 2022

2.1.5, March 2019

6.8, April 2020

10.4, October 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

extended commercial license available

commercial

Some plugins of GraphDB Workbench are open sourced

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.

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Implementation language

C++

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux
OS X

All OS with a Java VM
Linux
OS X
Windows

hosted

Data scheme

yes

schema-free

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

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

yes

JSON 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.

Secondary indexes

yes

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

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like DML and DDL statements

SPARQL is used as query language

SQL-like DML and DDL statements (CQL); Spark SQL

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

SQL-like query language

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

well-defined plugin interfaces; JavaScript server-side extensibility

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

configurable replication factor, datacenter aware, advanced replication for edge computing

Multi-source replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

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

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Constraint checking

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Security and Authentication via Web Application Container (Tomcat, Jetty)

Access rights for users can be defined per object

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.

Access rights can be defined down to the item level

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Ontotext GraphDB is a semantic database engine that allows organizations to build...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
» more

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

Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
» more

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

Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more

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

Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more

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

Licensing and pricing models

Annual subscription
» more

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

News

Case study: Policy Enforcement Automation With Semantics
2 May 2024

Okay, RAG… We Have a Problem
26 April 2024

Scaling Understanding with the Help of Feedback Loops, Knowledge Graphs and NLP
19 April 2024

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.