DBMS > ArangoDB vs. Brytlyt vs. Google BigQuery vs. HEAVY.AI vs. Netezza

System Properties Comparison ArangoDB vs. Brytlyt vs. Google BigQuery vs. HEAVY.AI vs. Netezza

Editorial information provided by DB-Engines

Name

Description

Native multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Large scale data warehouse service with append-only tables

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Document store
Graph DBMS
Key-value store
Search engine

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	3.30
Rank	#82	Overall
	#14	Document stores
	#5	Graph DBMS
	#10	Key-value stores
	#10	Search engines

Score	0.27
Rank	#292	Overall
	#132	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Website

arangodb.com

brytlyt.io

cloud.google.com/bigquery

github.com/heavyai/heavydb
www.heavy.ai

www.ibm.com/products/netezza

Technical documentation

docs.arangodb.com

docs.brytlyt.io

cloud.google.com/bigquery/docs

docs.heavy.ai

Social network pages

Developer

ArangoDB Inc.

Brytlyt

Google

HEAVY.AI, Inc.

IBM

Initial release

2012

2016

2010

2016

2000

Current release

3.11.5, November 2023

5.0, August 2023

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial license (Enterprise) available

commercial

Open Source

Apache Version 2; enterprise edition 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.

ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour.

Implementation language

C++

C, C++ and CUDA

C++ and CUDA

Server operating systems

Linux
OS X
Windows

hosted

Linux

included in appliance

Data scheme

schema-free

automatically recognizes schema within a collection

yes

Typing

predefined data types such as float or date

yes

string, double, boolean, list, hash

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
OLE DB

Supported programming languages

C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

JavaScript

user defined functions

in PL/pgSQL

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

since version 2.0

none

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with configurable replication factor

Source-replica replication

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be done with stored procedures in JavaScript

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

configurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

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

yes

fine grained access rights according to SQL-standard

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

Users with fine-grained authorization concept

More information provided by the system vendor

Specific characteristics

Graph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more

Competitive advantages

Consolidation: As a native multi-model database, can be used as a full blown document...
» more

Typical application scenarios

Native multi-model in ArangoDB is being used for a broad range of projects across...
» more

Key customers

Cisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more

Market metrics

ArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more

Licensing and pricing models

Very permissive Apache 2 License for Community Edition & commercial licenses are...
» more

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