DBMS > Google Cloud Spanner vs. Microsoft SQL Server vs. OpenEdge vs. RavenDB vs. Sequoiadb

System Properties Comparison Google Cloud Spanner vs. Microsoft SQL Server vs. OpenEdge vs. RavenDB vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Microsofts flagship relational DBMS

Application development environment with integrated database management system

Open Source Operational and Transactional Enterprise NoSQL Document Database

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Document store

Document store
Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

Score	2.68
Rank	#102	Overall
	#19	Document stores

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Website

cloud.google.com/spanner

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

www.progress.com/openedge

ravendb.net

www.sequoiadb.com

Technical documentation

cloud.google.com/spanner/docs

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

documentation.progress.com/output/ua/OpenEdge_latest

ravendb.net/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Google

Microsoft

Progress Software Corporation

Hibernating Rhinos

Sequoiadb Ltd.

Initial release

2017

1989

1984

2010

2013

Current release

SQL Server 2022, November 2022

OpenEdge 12.2, March 2020

5.4, July 2022

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

AGPL version 3, commercial license available

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

hosted

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

Query statements complying to ANSI 2011

yes

close to SQL 92

SQL-like query language (RQL)

SQL-like query language

APIs and other access methods

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

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

JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

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

Progress proprietary ABL (Advanced Business Language)

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

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

yes

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

horizontal partitioning

since Version 11.4

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

yes, but depending on the SQL-Server Edition

Source-replica replication

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Eventual Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

ACID, Cluster-wide transaction available

Document is locked during a transaction

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 for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Users and groups

Authorization levels configured per client per database

simple password-based access control

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