DBMS > Google Cloud Spanner vs. Kyligence Enterprise vs. Lovefield vs. Sequoiadb vs. SiteWhere

System Properties Comparison Google Cloud Spanner vs. Kyligence Enterprise vs. Lovefield vs. Sequoiadb vs. SiteWhere

Editorial information provided by DB-Engines

Name

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.

A distributed analytics engine for big data, built on top of Apache Kylin

Embeddable relational database for web apps written in pure JavaScript

NewSQL database with distributed OLTP and SQL

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Document store
Relational DBMS

Time Series DBMS

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

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

cloud.google.com/spanner

kyligence.io/kyligence-enterprise

google.github.io/lovefield

www.sequoiadb.com

github.com/sitewhere/sitewhere

Technical documentation

cloud.google.com/spanner/docs

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

www.sequoiadb.com/en/index.php?m=Files&a=index

sitewhere1.sitewhere.io/index.html

Developer

Google

Kyligence, Inc.

Google

Sequoiadb Ltd.

SiteWhere

Initial release

2017

2016

2014

2013

2010

Current release

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Server: AGPL; Client: Apache V2

Open Source

Common Public Attribution License Version 1.0

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

C++

Java

Server operating systems

hosted

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

via JavaScript builder pattern

SQL-like query language

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

JDBC
ODBC
RESTful HTTP API

proprietary protocol using JSON

HTTP REST

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

JavaScript

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

none

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

Document is locked during a transaction

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

User concepts

Access control

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

simple password-based access control

Users with fine-grained authorization concept

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More resources

Recent citations in the news

Google Improves Cloud Spanner: More Compute and Storage without Price Increase
14 October 2023, InfoQ.com

Google makes its Cloud Spanner database service faster and more cost-efficient
11 October 2023, SiliconANGLE News

Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB
11 October 2023, TechCrunch

Google Cloud just fired a major volley at AWS as the cloud wars heat up
12 October 2023, TechRadar

Google Spanner: When Do You Need to Move to It?
11 September 2023, hackernoon.com

provided by Google News

Kyligence Grows OLAP Business in the Cloud
20 February 2020, Datanami

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10 August 2021, VentureBeat

Distributed OLAPer Kyligence accelerates core engine, adds real-time data support – Blocks and Files
10 August 2021, Blocks & Files

How Kyligence Cloud uses Amazon EMR Serverless to simplify OLAP | Amazon Web Services
9 November 2022, AWS Blog

The 10 Hottest Big Data Tools Of 2023
23 November 2023, CRN

provided by Google News

SiteWhere: An open platform for connected devices
11 July 2017, Open Source For You

Ten Popular IoT Platforms You Should be Aware of
27 March 2023, Open Source For You

11 Best Open source IoT Platforms To Develop Smart Projects
9 March 2023, H2S Media

provided by Google News

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