DBMS > Google BigQuery vs. GridGain vs. Kdb vs. Neo4j vs. Stardog

System Properties Comparison Google BigQuery vs. GridGain vs. Kdb vs. Neo4j vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

GridGain is an in-memory computing platform, built on Apache Ignite

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS
Vector DBMS

Graph DBMS

Graph DBMS
RDF store

Secondary database models

Relational DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	44.46
Rank	#23	Overall
	#1	Graph DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

cloud.google.com/bigquery

Technical documentation

cloud.google.com/bigquery/docs

www.gridgain.com/docs/index.html

code.kx.com

neo4j.com/docs

docs.stardog.com

Developer

Google

GridGain Systems, Inc.

Kx Systems, a division of First Derivatives plc

Neo4j, Inc.

Stardog-Union

Initial release

2010

2007

2000

kdb was released 2000, kdb+ in 2003

2007

2010

Current release

GridGain 8.5.1

3.6, May 2018

5.19, April 2024

7.3.0, May 2020

License

Commercial or Open Source

commercial

free 32-bit version

Open Source

GPL version3, commercial licenses available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++, .Net

Java, Scala

Java

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux

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

Linux
macOS
Windows

Data scheme

yes

schema-free and schema-optional

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

table attribute 'grouped'

yes

pluggable indexing subsystem, by default Apache Lucene

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

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

SQL-like query language (q)

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

RESTful HTTP/JSON API

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

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

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

user defined functions

yes

User defined Procedures and Functions

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes (cache interceptors and events)

yes

with views

yes

via event handler

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

yes using Neo4j Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Source-replica replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

relationships in graphs

Transaction concepts

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

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

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

Google Cloud Identity & Access Management (IAM)

Security Hooks for custom implementations

rights management via user accounts

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

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Neo4j delivers graph technology that has been battle tested for performance and scale...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Neo4j is the market leader, graph database category creator, and the most widely...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Real-Time Recommendations Master Data Management Identity and Access Management Network...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
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Licensing and pricing models

upon request
» more

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.