DBMS > Amazon DocumentDB vs. BigObject vs. Hypertable vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. BigObject vs. Hypertable vs. Yaacomo

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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.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

Analytic DBMS for real-time computations and queries

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store

Relational DBMS

a hierachical model (tree) can be imposed

Wide column store

Relational DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Website

aws.amazon.com/documentdb

bigobject.io

yaacomo.com

Technical documentation

aws.amazon.com/documentdb/resources

docs.bigobject.io

Developer

BigObject, Inc.

Hypertable Inc.

Q2WEB GmbH

Initial release

2019

2015

2009

Current release

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

free community edition available

Open Source

GNU version 3. Commercial license available

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

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Windows

an inofficial Windows port is available

Android
Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

fluentd
ODBC
RESTful HTTP API

C++ API
Thrift

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

selectable replication factor on file system level

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

fine grained access rights according to SQL-standard

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More resources

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