DBMS > Graph Engine vs. IBM Db2 warehouse vs. MarkLogic vs. Snowflake vs. YDB

System Properties Comparison Graph Engine vs. IBM Db2 warehouse vs. MarkLogic vs. Snowflake vs. YDB

Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Cloud-based data warehousing service

Operational and transactional Enterprise NoSQL database

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

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

Graph DBMS
Key-value store

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Document store
Relational DBMS

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

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

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

Website

www.graphengine.io

www.ibm.com/products/db2/warehouse

www.marklogic.com

www.snowflake.com

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

Technical documentation

www.graphengine.io/docs/manual

docs.marklogic.com

docs.snowflake.net/manuals/index.html

ydb.tech/en/docs

Developer

Microsoft

IBM

MarkLogic Corp.

Snowflake Computing Inc.

Yandex

Initial release

2010

2014

2001

2014

2019

Current release

11.0, December 2022

License

Commercial or Open Source

Open Source

MIT License

commercial

restricted free version is available

commercial

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

.NET and C

C++

Server operating systems

.NET

hosted

Linux
OS X
Windows

hosted

Linux

Data scheme

yes

schema-free

Schema can be enforced

yes

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

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

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

yes

SQL-like query language (YQL)

APIs and other access methods

RESTful HTTP API

.NET Client API
JDBC
ODBC
OLE DB

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

CLI Client
JDBC
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

C#
C++
F#
Visual Basic

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

PL/SQL, SQL PL

yes

via XQuery or JavaScript

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes

yes, with Range Indexes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control at the document and subdocument levels

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

Access rights defined for Yandex Cloud users

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