DBMS > AgensGraph vs. Dolt vs. Google BigQuery vs. Yaacomo

System Properties Comparison AgensGraph vs. Dolt vs. Google BigQuery vs. Yaacomo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

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

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

A MySQL compatible DBMS with Git-like versioning of data and schema

Large scale data warehouse service with append-only tables

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

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Website

bitnine.net/agensgraph

github.com/dolthub/dolt
www.dolthub.com

cloud.google.com/bigquery

yaacomo.com

Technical documentation

bitnine.net/documentation

docs.dolthub.com

cloud.google.com/bigquery/docs

Developer

Bitnine Global Inc.

DoltHub Inc

Google

Q2WEB GmbH

Initial release

2016

2018

2010

2009

Current release

2.1, December 2018

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

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

Server operating systems

Linux
OS X
Windows

Linux
macOS
Windows

hosted

Android
Linux
Windows

Data scheme

depending on used data model

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

SQL

Support of SQL

yes

APIs and other access methods

Cypher Query Language
JDBC

CLI Client
HTTP REST

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

currently in alpha release

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

Only one user is configurable, and must be specified in the config file at startup

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.