DBMS > Google Cloud Spanner vs. Hawkular Metrics vs. HyperSQL vs. Lovefield vs. Yaacomo

System Properties Comparison Google Cloud Spanner vs. Hawkular Metrics vs. HyperSQL vs. Lovefield vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Embeddable relational database for web apps written in pure JavaScript

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

cloud.google.com/spanner

www.hawkular.org

hsqldb.org

google.github.io/lovefield

yaacomo.com

Technical documentation

cloud.google.com/spanner/docs

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

hsqldb.org/web/hsqlDocsFrame.html

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Google

Community supported by Red Hat

Google

Q2WEB GmbH

Initial release

2017

2014

2001

2014

2009

Current release

2.7.2, June 2023

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

based on BSD license

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

JavaScript

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Android
Linux
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP REST

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

Go
Java
Python
Ruby

All languages supporting JDBC/ODBC
Java

JavaScript

Server-side scripts

Stored procedures

Java, SQL

Triggers

yes

via Hawkular Alerting

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

selectable replication factor

based on Cassandra

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

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31 May 2024, Data Center Knowledge

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14 October 2023, InfoQ.com

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