DBMS > Microsoft Azure Data Explorer vs. PieCloudDB vs. TypeDB

System Properties Comparison Microsoft Azure Data Explorer vs. PieCloudDB vs. TypeDB

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Editorial information provided by DB-Engines

Name

Description

Fully managed big data interactive analytics platform

A cloud-native analytic database platform with new technologoy for elastic MPP

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Relational DBMS

column oriented

Relational DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.25
Rank	#304	Overall
	#138	Relational DBMS

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

azure.microsoft.com/services/data-explorer

www.openpie.com

typedb.com

Technical documentation

docs.microsoft.com/en-us/azure/data-explorer

typedb.com/docs

Developer

Microsoft

OpenPie

Vaticle

Initial release

2019

2016

Current release

cloud service with continuous releases

2.1, January 2023

2.26.3, January 2024

License

Commercial or Open Source

commercial

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

Java

Server operating systems

hosted

Linux
OS X
Windows

Data scheme

Fixed schema with schema-less datatypes (dynamic)

yes

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-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.

yes

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

CLI Client
JDBC
ODBC

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Java
PL/SQL
Python
R

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

user defined functions

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Azure Active Directory Authentication

User Roles and pluggable authentication with full SQL Standard

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

PieCloudDB, OpenPie's flagship product, is a cutting-edge cloud-native data warehouse....
» more

TypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more

Competitive advantages

Extreme Elastic: PieCloudDB utilizes a cutting-edge eMPP cloud-native architecture...
» more

TypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more

Typical application scenarios

PieCloudDB is ideal for Data mining applications that require extreme scalability...
» more

Life sciences : TypeDB makes working with biological data much easier and accelerates...
» more

Key customers

Sail-Cloud China Shipbuilding Group Haizhou System Soochow Securities etc.,
» more

Licensing and pricing models

PieCloudDB Community Edition: Community License, Free Download, Self-Hosted Deployment；...
» more

Apache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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

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