DBMS > Cachelot.io vs. Google Cloud Spanner vs. Hawkular Metrics vs. Postgres-XL

System Properties Comparison Cachelot.io vs. Google Cloud Spanner vs. Hawkular Metrics vs. Postgres-XL

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Editorial information provided by DB-Engines
Name	Cachelot.io  Xexclude from comparison	Google Cloud Spanner  Xexclude from comparison	Hawkular Metrics  Xexclude from comparison	Postgres-XL  Xexclude from comparison
Description	In-memory caching system	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.	Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database model	Key-value store	Relational DBMS	Time Series DBMS	Relational DBMS
Secondary database models				Document store Spatial DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 0.04 Rank #388   Overall #62   Key-value stores	Score 2.84 Rank #100   Overall #51   Relational DBMS	Score 0.08 Rank #366   Overall #39   Time Series DBMS	Score 0.53 Rank #254   Overall #117   Relational DBMS
Website	cachelot.io	cloud.google.com/­spanner	www.hawkular.org	www.postgres-xl.org
Technical documentation		cloud.google.com/­spanner/­docs	www.hawkular.org/­hawkular-metrics/­docs/­user-guide	www.postgres-xl.org/­documentation
Developer		Google	Community supported by Red Hat
Initial release	2015	2017	2014	2014 since 2012, originally named StormDB
Current release				10 R1, October 2018
License Commercial or Open Source	Open Source Simplified BSD License	commercial	Open Source Apache 2.0	Open Source Mozilla public license
Cloud-based only Only available as a cloud service	no	yes	no	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	C++		Java	C
Server operating systems	FreeBSD Linux OS X	hosted	Linux OS X Windows	Linux macOS
Data scheme	schema-free	yes	schema-free	yes
Typing predefined data types such as float or date	no	yes	yes	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.	no	no	no	yes XML type, but no XML query functionality
Secondary indexes	no	yes	no	yes
SQL Support of SQL	no	yes Query statements complying to ANSI 2011	no	yes distributed, parallel query execution
APIs and other access methods	Memcached protocol	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	ADO.NET JDBC native C library ODBC streaming API for large objects
Supported programming languages	.Net C C++ ColdFusion Erlang Java Lisp Lua OCaml OCaml Perl PHP Python Ruby	Go Java JavaScript (Node.js) Python	Go Java Python Ruby	.Net C C++ Delphi Erlang Java JavaScript (Node.js) Perl PHP Python Tcl
Server-side scripts Stored procedures	no	no	no	user defined functions
Triggers	no	no	yes via Hawkular Alerting	yes
Partitioning methods Methods for storing different data on different nodes	none	Sharding	Sharding based on Cassandra	horizontal partitioning
Replication methods Methods for redundantly storing data on multiple nodes	none	Multi-source replication with 3 replicas for regional instances.	selectable replication factor based on Cassandra
MapReduce Offers an API for user-defined Map/Reduce methods	no	yes using Google Cloud Dataflow	no	no
Consistency concepts Methods to ensure consistency in a distributed system	none	Immediate Consistency	Eventual Consistency based on Cassandra Immediate Consistency based on Cassandra	Immediate Consistency
Foreign keys Referential integrity	no	yes by using interleaved tables, this features focuses more on performance improvements than on referential integrity	no	yes
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	no	ACID Strict serializable isolation	no	ACID MVCC
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	no	yes	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	no	no	no	no
User concepts Access control	no	Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)	no	fine grained access rights according to SQL-standard
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More resources
	Cachelot.io	Google Cloud Spanner	Hawkular Metrics	Postgres-XL
Recent citations in the news		Google Improves Cloud Spanner: More Compute and Storage without Price Increase 14 October 2023, InfoQ.com Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB 11 October 2023, TechCrunch Google makes its Cloud Spanner database service faster and more cost-efficient 11 October 2023, SiliconANGLE News Google Spanner: When Do You Need to Move to It? 11 September 2023, hackernoon.com Google Cloud Spanner Is Now Half the Cost of Amazon DynamoDB 13 October 2023, Datanami provided by Google News	Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS 5 June 2019, DevClass provided by Google News

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