DBMS > Google BigQuery vs. Hive vs. Ignite vs. Neo4j vs. Postgres-XL

System Properties Comparison Google BigQuery vs. Hive vs. Ignite vs. Neo4j vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

cloud.google.com/bigquery

Technical documentation

cloud.google.com/bigquery/docs

cwiki.apache.org/confluence/display/Hive/Home

apacheignite.readme.io/docs

neo4j.com/docs

www.postgres-xl.org/documentation

Developer

Google

Apache Software Foundation

initially developed by Facebook

Apache Software Foundation

Neo4j, Inc.

Initial release

2010

2012

2015

2007

2014

since 2012, originally named StormDB

Current release

3.1.3, April 2022

Apache Ignite 2.6

5.20, May 2024

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

GPL version3, commercial licenses available

Open Source

Mozilla public license

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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

Java

C++, Java, .Net

Java, Scala

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

Linux
macOS

Data scheme

yes

schema-free and schema-optional

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

pluggable indexing subsystem, by default Apache Lucene

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

ANSI-99 for query and DML statements, subset of DDL

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
Thrift

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

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

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
PHP
Python

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

user defined functions and integration of map-reduce

yes (compute grid and cache interceptors can be used instead)

yes

User defined Procedures and Functions

user defined functions

Triggers

yes (cache interceptors and events)

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes using Neo4j Fabric

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes (replicated cache)

Causal Clustering using Raft protocol

available in in Enterprise Version only

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

MVCC

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

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

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles

Security Hooks for custom implementations

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Neo4j delivers graph technology that has been battle tested for performance and scale...
» more

Competitive advantages

Neo4j is the market leader, graph database category creator, and the most widely...
» more

Typical application scenarios

Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more

Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more

Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more

Licensing and pricing models

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more

News

This Week in Neo4j: Podcast, Testing, Knowledge Graph, GenAI and more
8 June 2024

Neo4j and Snowflake Bring Graph Data Science Into the AI Data Cloud
4 June 2024

RDF vs. Property Graphs: Choosing the Right Approach for Implementing a Knowledge Graph
4 June 2024

This Week in Neo4j: Importing Data, NODES, GenAI, Going Meta and more
1 June 2024

openCypher Will Pave the Road to GQL for Cypher Implementers
22 May 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.