DBMS > Google BigQuery vs. IBM Db2 Event Store vs. InfluxDB vs. Quasardb

System Properties Comparison Google BigQuery vs. IBM Db2 Event Store vs. InfluxDB vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Distributed Event Store optimized for Internet of Things use cases

DBMS for storing time series, events and metrics

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

cloud.google.com/bigquery

www.ibm.com/products/db2-event-store

www.influxdata.com/products/influxdb-overview

quasar.ai

Technical documentation

cloud.google.com/bigquery/docs

www.ibm.com/docs/en/db2-event-store

docs.influxdata.com/influxdb

doc.quasar.ai/master

Developer

Google

IBM

quasardb

Initial release

2010

2017

2013

2009

Current release

2.0

2.7.6, April 2024

3.14.1, January 2024

License

Commercial or Open Source

commercial

free developer edition available

Open Source

MIT-License; commercial enterprise version available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

C and C++

C++

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X

through Homebrew

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

integer and binary

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.

Secondary indexes

yes

with tags

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API
JSON over UDP

HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

selectable replication factor

in enterprise version only

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

by using LevelDB

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

yes

Transient mode

User concepts

Access control

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

simple rights management via user accounts

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

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