DBMS > BigObject vs. Blueflood vs. Dgraph vs. Google Cloud Bigtable

System Properties Comparison BigObject vs. Blueflood vs. Dgraph vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Scalable TimeSeries DBMS based on Cassandra

Distributed and scalable native Graph DBMS

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Graph DBMS

Key-value store
Wide column store

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Website

bigobject.io

blueflood.io

dgraph.io

cloud.google.com/bigtable

Technical documentation

docs.bigobject.io

github.com/rax-maas/blueflood/wiki

dgraph.io/docs

cloud.google.com/bigtable/docs

Developer

BigObject, Inc.

Rackspace

Dgraph Labs, Inc.

Google

Initial release

2015

2013

2016

2015

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Apache 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

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X

Linux
OS X
Windows

hosted

Data scheme

yes

predefined scheme

schema-free

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

SQL-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HTTP REST

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Supported programming languages

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

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

Server-side scripts

Stored procedures

Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

Synchronous replication via Raft

Internal replication in Colossus, and regional replication between two clusters in different zones

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID

Atomic single-row operations

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

Planned for future releases

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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