DBMS > Amazon Aurora vs. Hypertable vs. STSdb

System Properties Comparison Amazon Aurora vs. Hypertable vs. STSdb

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Fully managed relational database service built for the cloud providing unparalleled high performance and availability at global scale for MySQL, PostgreSQL, and DSQL

An open source BigTable implementation based on distributed file systems such as Hadoop

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Wide column store

Key-value store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	7.33
Rank	#46	Overall
	#29	Relational DBMS

Score	0.03
Rank	#361	Overall
	#55	Key-value stores

Website

aws.amazon.com/rds/aurora

github.com/STSSoft/STSdb4

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_AuroraOverview.html
docs.aws.amazon.com/aurora-dsql/latest/userguide/what-is-aurora-dsql.html

Social network pages

Developer

Amazon

Hypertable Inc.

STS Soft SC

Initial release

2015

2009

2011

Current release

Aurora DSQL, November 2024 (preview), PostgreSQL: docs.aws.amazon.com/AmazonRDS/latest/AuroraPostgreSQLReleaseNotes/AuroraPostgreSQL.Updates.html , MySQL: docs.aws.amazon.com/AmazonRDS/latest/AuroraMySQLReleaseNotes/AuroraMySQL.release-calendars.html

0.9.8.11, March 2016

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

Open Source

GPLv2, 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

PostgreSQL/MySQL: C, C++, Aurora DSQL: Rust

C++

Server operating systems

Amazon Linux

Linux
OS X
Windows

an inofficial Windows port is available

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes, MySQL and PostgreSQL dialects

APIs and other access methods

DSQL API: docs.aws.amazon.com/aurora-dsql/latest/userguide/CHAP_api_reference.html
MySQL wire protocol
PostgreSQL wire protocol
RDS Data API: docs.aws.amazon.com/AmazonRDS/latest/UserGuide/ProgrammingGuide.html

C++ API
Thrift

.NET Client API

Supported programming languages

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

C++
Java
Perl
PHP
Python
Ruby

C#
Java

Server-side scripts

Stored procedures

PL/pgSQL, MySQL stored program language, APG trusted language extensions

Triggers

Aurora MySQL: Yes. Aurora PostgreSQL: Yes. Aurora DSQL: No.

Partitioning methods

Methods for storing different data on different nodes

DBMS table partitioning, Horizontal storage partitioning, Sharding, Distributed horizontal partitioning (DSQL)

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Full replication
Logical replication
Snapshot replication
Transactional replication

selectable replication factor on file system level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate/Strong Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID, Multi-statement

Concurrency

Support for concurrent manipulation of data

Multiversion concurrency control (MVCC) with fully compatible MySQL and PostgreSQL options. Optimistic concurrency control (OCC) in Aurora DSQL.

yes

Durability

Support for making data persistent

Data is replicated across 3 Availability Zones (AZs) within a single AWS Region. Active-active multi-Region high availability across 3 Regions (2 active, 1 witness) and automated failover recovery with Aurora DSQL. Automated, continuous backup of data with point in time restore. Fault-tolerant, self-healing storage system.

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

Role based permissions
Row level security

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