DBMS > GBase vs. Microsoft SQL Server vs. Riak KV vs. SAP HANA vs. YDB

System Properties Comparison GBase vs. Microsoft SQL Server vs. Riak KV vs. SAP HANA vs. YDB

Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Microsofts flagship relational DBMS

Distributed, fault tolerant key-value store

In-memory, column based data store. Available as appliance or cloud service

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

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

www.gbase.cn

www.microsoft.com/en-us/sql-server

www.sap.com/products/hana.html

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

Technical documentation

learn.microsoft.com/en-US/sql/sql-server

www.tiot.jp/riak-docs/riak/kv/latest

help.sap.com/hana

ydb.tech/en/docs

Developer

General Data Technology Co., Ltd.

Microsoft

OpenSource, formerly Basho Technologies

SAP

Yandex

Initial release

2004

1989

2009

2010

2019

Current release

GBase 8a, GBase 8s, GBase 8c

SQL Server 2022, November 2022

3.2.0, December 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache version 2, commercial enterprise edition

commercial

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

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Implementation language

C, Java, Python

C++

Erlang

Server operating systems

Linux

Linux
Windows

Linux
OS X

Appliance or cloud-service

Linux

Data scheme

yes

schema-free

yes

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.

yes

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

Standard with numerous extensions

yes

SQL-like query language (YQL)

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API
Native Erlang Interface

JDBC
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Erlang

SQLScript, R

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

no "single point of failure"

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

selectable replication factor

yes

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

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.

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

yes, using Riak Security

yes

Access rights defined for Yandex Cloud users

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