DBMS > Amazon SimpleDB vs. Google BigQuery vs. Vitess vs. YugabyteDB

System Properties Comparison Amazon SimpleDB vs. Google BigQuery vs. Vitess vs. YugabyteDB

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Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Large scale data warehouse service with append-only tables

Scalable, distributed, cloud-native DBMS, extending MySQL

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Wide column store

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

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Score	2.91
Rank	#102	Overall
	#51	Relational DBMS

Website

aws.amazon.com/simpledb

cloud.google.com/bigquery

vitess.io

www.yugabyte.com

Technical documentation

docs.aws.amazon.com/simpledb

cloud.google.com/bigquery/docs

vitess.io/docs

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Amazon

Google

The Linux Foundation, PlanetScale

Yugabyte Inc.

Initial release

2007

2010

2013

2017

Current release

15.0.2, December 2022

2.19, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0, commercial licenses available

Open Source

Apache 2.0

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.

YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.

Implementation language

C and C++

Server operating systems

hosted

Docker
Linux
macOS

Linux
OS X

Data scheme

schema-free

yes

depending on used data model

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.

Secondary indexes

yes

All columns are indexed automatically

yes

SQL

Support of SQL

yes

with proprietary extensions

yes, PostgreSQL compatible

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

ADO.NET
JDBC
MySQL protocol
ODBC

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

proprietary syntax

yes

sql, plpgsql, C

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

Sharding

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

Since BigQuery is designed for querying data

ACID at shard level

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

based on RocksDB

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 can be defined via the AWS Identity and Access Management (IAM)

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users with fine-grained authorization concept

no user groups or roles

yes

More information provided by the system vendor

Specific characteristics

YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more

Competitive advantages

PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
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Typical application scenarios

Systems of record and engagement for cloud native applications that require resilience,...
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Market metrics

2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
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Licensing and pricing models

Apache 2.0 license for the database
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