DBMS > Blazegraph vs. CockroachDB vs. Google BigQuery vs. Newts vs. SAP Advantage Database Server

System Properties Comparison Blazegraph vs. CockroachDB vs. Google BigQuery vs. Newts vs. SAP Advantage Database Server

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.

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Large scale data warehouse service with append-only tables

Time Series DBMS based on Cassandra

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

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

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

blazegraph.com

www.cockroachlabs.com

cloud.google.com/bigquery

opennms.github.io/newts

www.sap.com/products/advantage-database-server.html

Technical documentation

wiki.blazegraph.com

www.cockroachlabs.com/docs

cloud.google.com/bigquery/docs

github.com/OpenNMS/newts/wiki

Developer

Blazegraph

Cockroach Labs

Google

OpenNMS Group

Sybase, SAP

Initial release

2006

2015

2010

2014

1993

Current release

2.1.5, March 2019

23.1.1, May 2023

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

Apache 2.0, commercial license available

commercial

Open Source

Apache 2.0

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

Java

Server operating systems

Linux
OS X
Windows

Linux
macOS
Windows

hosted

Linux
OS X
Windows

Linux
Windows

Data scheme

schema-free

dynamic schema

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

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.

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes, wire compatible with PostgreSQL

yes

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

JDBC

RESTful HTTP/JSON API

HTTP REST
Java API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

none

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using RAFT

selectable replication factor

based on Cassandra

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

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.

caching of (temporary) tables can be configured

User concepts

Access control

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

Role-based access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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