DBMS > Amazon Aurora vs. BigObject vs. Microsoft SQL Server vs. NebulaGraph vs. Vertica

System Properties Comparison Amazon Aurora vs. BigObject vs. Microsoft SQL Server vs. NebulaGraph vs. Vertica

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Analytic DBMS for real-time computations and queries

Microsofts flagship relational DBMS

A distributed, linear scalable, high perfomant Graph DBMS

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Graph DBMS

Relational DBMS

Column oriented

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	7.57
Rank	#51	Overall
	#32	Relational DBMS

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.23
Rank	#116	Overall
	#10	Graph DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

aws.amazon.com/rds/aurora

bigobject.io

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

github.com/vesoft-inc/nebula
www.nebula-graph.io

www.vertica.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

docs.bigobject.io

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

docs.nebula-graph.io

vertica.com/documentation

Developer

Amazon

BigObject, Inc.

Microsoft

Vesoft Inc.

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2015

1989

2019

2005

Current release

SQL Server 2022, November 2022

12.0.3, January 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

restricted free version is available

Open Source

Apache Version 2.0 + Common Clause 1.0

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Windows

Linux

Data scheme

yes

Strong typed schema

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

Nebula Graph internally uses the Key-Value store RocksDB for persistency. The vertices, edges, and their properties are stored as Key while their values are stored as Value. The primary indexes are per Key and secondary indexes are per Value.

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

SQL-like query language

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

ADO.NET
JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

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

Browser interface
console (shell)
Cypher Query Language
GO Object Graph Mapper
Java Object Graph Mapper
NGBatis

ORM framework for NebulaGraph and Spring-Boot
Proprietary native API
Python Object Graph Mapper
Query language nGQL

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

.Net
C++
Go
Java
PHP
Python

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

Server-side scripts

Stored procedures

yes

Lua

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

user defined functions

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

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

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes, but depending on the SQL-Server Edition

Causal Clustering using Raft protocol

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

using RocksDB

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

fine grained access rights according to SQL-standard

Role-based access control

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.