DBMS > AnzoGraph DB vs. Blueflood vs. IBM Db2 warehouse vs. Snowflake vs. Spark SQL

System Properties Comparison AnzoGraph DB vs. Blueflood vs. IBM Db2 warehouse vs. Snowflake vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Scalable TimeSeries DBMS based on Cassandra

Cloud-based data warehousing service

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Relational DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

cambridgesemantics.com/anzograph

blueflood.io

www.ibm.com/products/db2/warehouse

www.snowflake.com

spark.apache.org/sql

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

github.com/rax-maas/blueflood/wiki

docs.snowflake.net/manuals/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Cambridge Semantics

Rackspace

IBM

Snowflake Computing Inc.

Apache Software Foundation

Initial release

2018

2013

2014

Current release

2.3, January 2021

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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

Scala

Server operating systems

Linux

Linux
OS X

hosted

Linux
OS X
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

predefined scheme

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

SQL-like DML and DDL statements

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

HTTP REST

.NET Client API
JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

JDBC
ODBC

Supported programming languages

C++
Java
Python

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript (Node.js)
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

PL/SQL, SQL PL

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

based on Cassandra

Sharding

yes

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication factor

based on Cassandra

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

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

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 and roles

fine grained access rights according to SQL-standard

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

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