DBMS > Hypertable vs. Microsoft Azure Cosmos DB vs. Quasardb vs. Sequoiadb vs. TimesTen

System Properties Comparison Hypertable vs. Microsoft Azure Cosmos DB vs. Quasardb vs. Sequoiadb vs. TimesTen

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

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

Globally distributed, horizontally scalable, multi-model database service

Distributed, high-performance timeseries database

NewSQL database with distributed OLTP and SQL

In-Memory RDBMS compatible to Oracle

Primary database model

Wide column store

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Document store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

azure.microsoft.com/services/cosmos-db

quasar.ai

www.sequoiadb.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

learn.microsoft.com/azure/cosmos-db

doc.quasar.ai/master

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

docs.oracle.com/database/timesten-18.1

Developer

Hypertable Inc.

Microsoft

quasardb

Sequoiadb Ltd.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2009

2014

2009

2013

1998

Current release

0.9.8.11, March 2016

3.14.1, January 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Server: AGPL; Client: Apache V2

commercial

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

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

hosted

BSD
Linux
OS X
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

integer and binary

yes

oid, date, timestamp, binary, regex

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

restricted

only exact value or prefix value scans

yes

All properties auto-indexed by default

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

C++ API
Thrift

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP API

proprietary protocol using JSON

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

.Net
C++
Java
PHP
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

JavaScript

PL/SQL

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

yes

Implicit feature of the cloud service

Source-replica replication with selectable replication factor

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

User concepts

Access control

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

simple password-based access control

fine grained access rights according to SQL-standard

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