DBMS > atoti vs. Blazegraph vs. Google BigQuery vs. InfluxDB vs. SQream DB

System Properties Comparison atoti vs. Blazegraph vs. Google BigQuery vs. InfluxDB vs. SQream DB

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

Large scale data warehouse service with append-only tables

DBMS for storing time series, events and metrics

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	0.45
Rank	#253	Overall
	#13	Object oriented DBMS

Score	0.74
Rank	#217	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	22.12
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.62
Rank	#234	Overall
	#109	Relational DBMS

Website

atoti.io

blazegraph.com

cloud.google.com/bigquery

www.influxdata.com/products/influxdb-overview

sqream.com

Technical documentation

docs.atoti.io

wiki.blazegraph.com

cloud.google.com/bigquery/docs

docs.influxdata.com/influxdb

docs.sqream.com

Developer

ActiveViam

Blazegraph

Google

SQream Technologies

Initial release

2006

2010

2013

2017

Current release

2.1.5, March 2019

2.7.6, April 2024

2022.1.6, December 2022

License

Commercial or Open Source

commercial

free versions available

Open Source

extended commercial license available

commercial

Open Source

MIT-License; commercial enterprise version 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

Java

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X

through Homebrew

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

Numeric data and Strings

yes, ANSI Standard SQL Types

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

Multidimensional Expressions (MDX)

SPARQL is used as query language

yes

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

RESTful HTTP/JSON API

HTTP API
JSON over UDP

.Net
JDBC
ODBC

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Python

yes

user defined functions

in JavaScript

user defined functions in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

none

Sharding

in enterprise version only

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

in enterprise version only

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

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, multi-version concurrency control (MVCC)

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

Depending on used storage engine

User concepts

Access control

Security and Authentication via Web Application Container (Tomcat, Jetty)

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

Google Cloud Identity & Access Management (IAM)

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more

Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
» more

News

Deploying InfluxDB and Telegraf to Monitor Kubernetes
17 September 2024

Telegraf 1.32 Release Notes
13 September 2024

An Introductory Guide to Cloud Security for IIoT
12 September 2024

Building Real-Time Android Apps with InfluxDB Cloud: Data Logging, Querying, and Visualization
10 September 2024

How to Use InfluxDB for Real-Time SpringBoot Application Monitoring
5 September 2024

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.