DBMS > AnzoGraph DB vs. Drizzle vs. IBM Db2 Event Store vs. Snowflake

System Properties Comparison AnzoGraph DB vs. Drizzle vs. IBM Db2 Event Store vs. Snowflake

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Distributed Event Store optimized for Internet of Things use cases

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

Primary database model

Graph DBMS
RDF store

Relational DBMS

Event 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	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.ibm.com/products/db2-event-store

www.snowflake.com

Technical documentation

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

www.ibm.com/docs/en/db2-event-store

docs.snowflake.net/manuals/index.html

Developer

Cambridge Semantics

Drizzle project, originally started by Brian Aker

IBM

Snowflake Computing Inc.

Initial release

2018

2008

2017

2014

Current release

2.3, January 2021

7.2.4, September 2012

2.0

License

Commercial or Open Source

commercial

free trial version available

Open Source

GNU GPL

commercial

free developer edition available

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++

C and C++

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux

Linux, macOS, Windows for the developer addition

hosted

Data scheme

Schema-free and OWL/RDFS-schema support

yes

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

yes

with proprietary extensions

yes

through the embedded Spark runtime

yes

APIs and other access methods

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

JDBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C++
Java
Python

C
C++
Java
PHP

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

user defined functions

Triggers

hooks for callbacks inside the server can be used.

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication
Source-replica replication

Active-active shard replication

yes

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

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

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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

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