DBMS > Ignite vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. YDB

System Properties Comparison Ignite vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. YDB

Editorial information provided by DB-Engines

Name

Description

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Globally distributed, horizontally scalable, multi-model database service

Fully managed big data interactive analytics platform

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

column oriented

Relational DBMS

Document store
Relational DBMS

Secondary database models

Spatial DBMS

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	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	5.16
Rank	#69	Overall
	#37	Relational DBMS

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Score	0.34
Rank	#285	Overall
	#43	Document stores
	#130	Relational DBMS

Website

ignite.apache.org

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/services/data-explorer

www.sadasengine.com

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

apacheignite.readme.io/docs

learn.microsoft.com/azure/cosmos-db

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

ydb.tech/en/docs

Developer

Apache Software Foundation

Microsoft

SADAS s.r.l.

Yandex

Initial release

2015

2014

2019

2006

2019

Current release

Apache Ignite 2.6

cloud service with continuous releases

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free trial version available

Open Source

Apache 2.0; commercial license 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, .Net

C++

Server operating systems

Linux
OS X
Solaris
Windows

hosted

AIX
Linux
Windows

Linux

Data scheme

yes

schema-free

Fixed schema with schema-less datatypes (dynamic)

yes

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

JSON types

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

yes

All properties auto-indexed by default

all fields are automatically indexed

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

Kusto Query Language (KQL), SQL subset

yes

SQL-like query language (YQL)

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

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

JDBC
ODBC
Proprietary protocol

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

JavaScript

Yes, possible languages: KQL, Python, R

Triggers

yes (cache interceptors and events)

JavaScript

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

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Implicit feature of the cloud service

yes

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

none

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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

managed by 'Learn by Usage'

User concepts

Access control

Security Hooks for custom implementations

Access rights can be defined down to the item level

Azure Active Directory Authentication

Access rights for users, groups and roles according to SQL-standard

Access rights defined for Yandex Cloud users

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