DBMS > Microsoft Azure Cosmos DB vs. Spark SQL vs. TerarkDB vs. YDB

System Properties Comparison Microsoft Azure Cosmos DB vs. Spark SQL vs. TerarkDB vs. YDB

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

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

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key-value store

Document store
Relational DBMS

Secondary database models

Spatial DBMS

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

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.35
Rank	#278	Overall
	#43	Document stores
	#127	Relational DBMS

Website

azure.microsoft.com/services/cosmos-db

spark.apache.org/sql

github.com/bytedance/terarkdb

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

Technical documentation

learn.microsoft.com/azure/cosmos-db

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

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

ydb.tech/en/docs

Developer

Microsoft

Apache Software Foundation

ByteDance, originally Terark

Yandex

Initial release

2014

2016

2019

Current release

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

restricted open source 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

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Implementation language

Scala

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

schema-free

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

Typing

predefined data types such as float or date

yes

JSON 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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

SQL-like query language (YQL)

APIs and other access methods

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

JDBC
ODBC

C++ API
Java API

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

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

Java
Python
R
Scala

C++
Java

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes, utilizing Spark Core

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

User concepts

Access control

Access rights can be defined down to the item level

Access rights defined for Yandex Cloud users

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