DBMS > Alibaba Cloud PolarDB vs. AnzoGraph DB vs. Drizzle vs. NSDb vs. TypeDB

System Properties Comparison Alibaba Cloud PolarDB vs. AnzoGraph DB vs. Drizzle vs. NSDb vs. TypeDB

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

A cloud-native relational database compatible with MySQL, PostgreSQL, and Oracle. Designed for business critical applications.

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.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

TypeDB provides developers with an expressive, customizable type system to manage their data using an award-winning query language, TypeQL, while building on a high-performance, distributed architecture.

Primary database model

The type-theoretic data model of TypeDB subsumes the graph database model.
Object oriented DBMS

The data model of TypeDB comprises object-oriented features such as class inheritance and interfaces.
Relational DBMS

The type-theoretic data model of TypeDB subsumes the relational database model.

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

Score	0.82
Rank	#205	Overall
	#97	Relational DBMS

Score	0.22
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.65
Rank	#230	Overall
	#20	Graph DBMS
	#9	Object oriented DBMS
	#107	Relational DBMS

Website

www.alibabacloud.com/product/polardb

cambridgesemantics.com/anzograph

nsdb.io

typedb.com

Technical documentation

www.alibabacloud.com/help/en/polardb/product-overview

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

nsdb.io/Architecture

typedb.com/docs

Developer

Alibaba

Cambridge Semantics

Drizzle project, originally started by Brian Aker

Vaticle

Initial release

2018

2008

2017

2016

Current release

2.3, January 2021

7.2.4, September 2012

2.28.3, June 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

GNU GPL

Open Source

Apache Version 2.0

Open Source

GPL Version 3, commercial licenses available

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++

Java, Scala

Java

Server operating systems

hosted

Linux

FreeBSD
Linux
OS X

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

Schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

yes

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

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC

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

JDBC

gRPC
HTTP REST
WebSocket

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (IDE)

Supported programming languages

Java
Python

C++
Java
Python

C
C++
Java
PHP

Java
Scala

All JVM based languages
C
C++
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

Triggers

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication in MPP-Cluster

Multi-source replication
Source-replica replication

Synchronous replication via raft

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

Immediate Consistency in MPP-Cluster

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not needed in graphs

yes

substituted by the relationship feature

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

Using Apache Lucene

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

fine grained access rights according to SQL-standard

Access rights for users and roles

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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TypeDB provides a new level of expressivity, extensibility, interoperability, and...
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Typical application scenarios

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Licensing and pricing models

Specification and pricing. You can use either of the following billing methods to...
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Apache f or language drivers, and AGPL and Commercial for the database server. The...
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