DBMS > Google BigQuery vs. Hazelcast vs. IBM Db2 warehouse vs. InfluxDB vs. Linter

System Properties Comparison Google BigQuery vs. Hazelcast vs. IBM Db2 warehouse vs. InfluxDB vs. Linter

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A widely adopted in-memory data grid

Cloud-based data warehousing service

DBMS for storing time series, events and metrics

RDBMS for high security requirements

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS

with GEO package

Spatial DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Website

cloud.google.com/bigquery

hazelcast.com

www.ibm.com/products/db2/warehouse

www.influxdata.com/products/influxdb-overview

linter.ru

Technical documentation

cloud.google.com/bigquery/docs

hazelcast.org/imdg/docs

docs.influxdata.com/influxdb

Developer

Google

Hazelcast

IBM

relex.ru

Initial release

2010

2008

2014

2013

1990

Current release

5.3.6, November 2023

2.7.6, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses 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 and C++

Server operating systems

hosted

All OS with a Java VM

hosted

Linux
OS X

through Homebrew

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

the object must implement a serialization strategy

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

SQL-like query language

yes

APIs and other access methods

RESTful HTTP/JSON API

JCache
JPA
Memcached protocol
RESTful HTTP API

.NET Client API
JDBC
ODBC
OLE DB

HTTP API
JSON over UDP

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Event Listeners, Executor Services

PL/SQL, SQL PL

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

yes

selectable replication factor

in enterprise version only

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

one or two-phase-commit; repeatable reads; read commited

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

Depending on used storage engine

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Role-based access control

fine grained access rights according to SQL-standard

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

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