DBMS > Google BigQuery vs. Hawkular Metrics vs. IBM Db2 Event Store vs. Prometheus vs. SpaceTime

System Properties Comparison Google BigQuery vs. Hawkular Metrics vs. IBM Db2 Event Store vs. Prometheus vs. SpaceTime

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Distributed Event Store optimized for Internet of Things use cases

Open-source Time Series DBMS and monitoring system

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Relational DBMS

Time Series DBMS

Event Store
Time Series DBMS

Time Series DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Website

cloud.google.com/bigquery

www.hawkular.org

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

prometheus.io

www.mireo.com/spacetime

Technical documentation

cloud.google.com/bigquery/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

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

prometheus.io/docs

Developer

Google

Community supported by Red Hat

IBM

Mireo

Initial release

2010

2014

2017

2015

2020

Current release

2.0

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free developer edition available

Open Source

Apache 2.0

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++

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

SQL

Support of SQL

yes

through the embedded Spark runtime

A subset of ANSI SQL is implemented

APIs and other access methods

RESTful HTTP/JSON API

HTTP REST

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
Python
Ruby

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C#
C++
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Active-active shard replication

yes

by Federation

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

none

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

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

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)

fine grained access rights according to SQL-standard

yes

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