DBMS > 4D vs. Apache Druid vs. Google BigQuery vs. Kinetica vs. TerminusDB

System Properties Comparison 4D vs. Apache Druid vs. Google BigQuery vs. Kinetica vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Large scale data warehouse service with append-only tables

Fully vectorized database across both GPUs and CPUs

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Graph DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
RDF store

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

www.4d.com

druid.apache.org

cloud.google.com/bigquery

www.kinetica.com

terminusdb.com

Technical documentation

developer.4d.com

druid.apache.org/docs/latest/design

cloud.google.com/bigquery/docs

docs.kinetica.com

terminusdb.github.io/terminusdb/#

Developer

4D, Inc

Apache Software Foundation and contributors

Google

Kinetica

DataChemist Ltd.

Initial release

1984

2012

2010

2012

2018

Current release

v20, April 2023

29.0.1, April 2024

7.1, August 2021

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++

Prolog, Rust

Server operating systems

OS X
Windows

Linux
OS X
Unix

hosted

Linux

Data scheme

yes

schema-less columns are supported

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

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL for querying

yes

SQL-like DML and DDL statements

SQL-like query language (WOQL)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
RESTful HTTP/JSON API

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

4D proprietary IDE
PHP

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

JavaScript
Python

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

user defined functions

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

none

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, via HDFS, S3 or other storage engines

Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

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 journaling

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

User concepts

Access control

Users and groups

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles on table level

Role-based access control

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