DBMS > Amazon DocumentDB vs. Google Cloud Spanner vs. Microsoft SQL Server vs. Neo4j vs. Teradata Aster

System Properties Comparison Amazon DocumentDB vs. Google Cloud Spanner vs. Microsoft SQL Server vs. Neo4j vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Website

aws.amazon.com/documentdb

cloud.google.com/spanner

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

neo4j.com

Technical documentation

aws.amazon.com/documentdb/resources

cloud.google.com/spanner/docs

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

neo4j.com/docs

Developer

Google

Microsoft

Neo4j, Inc.

Teradata

Initial release

2019

2017

1989

2007

2005

Current release

SQL Server 2022, November 2022

5.20, May 2024

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPL version3, commercial licenses available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

C++

Java, Scala

Server operating systems

hosted

Linux
Windows

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free and schema-optional

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

pluggable indexing subsystem, by default Apache Lucene

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

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)

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Go
Java
JavaScript (Node.js)
Python

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

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

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

yes

User defined Procedures and Functions

R packages

Triggers

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

yes using Neo4j Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Multi-source replication with 3 replicas for regional instances.

yes, but depending on the SQL-Server Edition

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

using Google Cloud Dataflow

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

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

yes

Relationships in graphs

Transaction concepts

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

Atomic single-document operations

ACID

Strict serializable isolation

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 for users and roles

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, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
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Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
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Licensing and pricing models

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
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