DBMS > LevelDB vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. SAP SQL Anywhere vs. YDB

System Properties Comparison LevelDB vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. SAP SQL Anywhere vs. YDB

Editorial information provided by DB-Engines

Name

Description

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A Wide Column Store for rapid development using massive semi-structured datasets

Microsofts flagship relational DBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile 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

Wide column store

Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

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

Website

github.com/google/leveldb

azure.microsoft.com/en-us/services/storage/tables

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

www.sap.com/products/technology-platform/sql-anywhere.html

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

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

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

help.sap.com/docs/SAP_SQL_Anywhere

ydb.tech/en/docs

Developer

Google

Microsoft

SAP

formerly Sybase

Yandex

Initial release

2011

2012

1989

1992

2019

Current release

1.23, February 2021

SQL Server 2022, November 2022

17, July 2015

License

Commercial or Open Source

Open Source

BSD

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

C++

Server operating systems

Illumos
Linux
OS X
Windows

hosted

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

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

SQL

Support of SQL

yes

SQL-like query language (YQL)

APIs and other access methods

RESTful HTTP API

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

ADO.NET
HTTP API
JDBC
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

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

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

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

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

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

yes, but depending on the SQL-Server Edition

Source-replica replication

Database mirroring

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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 based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

Access rights defined for Yandex Cloud users

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