DBMS > Google BigQuery vs. Solr vs. SWC-DB vs. TempoIQ

System Properties Comparison Google BigQuery vs. Solr vs. SWC-DB vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Large scale data warehouse service with append-only tables

A widely used distributed, scalable search engine based on Apache Lucene

A high performance, scalable Wide Column DBMS

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

cloud.google.com/bigquery

solr.apache.org

github.com/kashirin-alex/swc-db
www.swcdb.org

tempoiq.com (offline)

Technical documentation

cloud.google.com/bigquery/docs

solr.apache.org/resources.html

Developer

Google

Apache Software Foundation

Alex Kashirin

TempoIQ

Initial release

2010

2006

2020

2012

Current release

9.5.0, February 2024

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

GPL V3

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++

Server operating systems

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Data scheme

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

Solr Parallel SQL Interface

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

Java API
RESTful HTTP/JSON API

Proprietary protocol
Thrift

HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C++

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java plugins

Triggers

yes

User configurable commands triggered on index changes

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

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

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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)

yes

simple authentication-based access control

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