DBMS > Google Cloud Bigtable vs. Spark SQL vs. TempoIQ

System Properties Comparison Google Cloud Bigtable vs. Spark SQL 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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Spark SQL is a component on top of 'Spark Core' for structured data processing

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

Primary database model

Key-value store
Wide column store

Relational DBMS

Time Series DBMS

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

Score	4.26
Rank	#86	Overall
	#14	Key-value stores
	#6	Wide column stores

Score	22.86
Rank	#35	Overall
	#21	Relational DBMS

Website

cloud.google.com/bigtable

spark.apache.org/sql

tempoiq.com (offline)

Technical documentation

cloud.google.com/bigtable/docs

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Google

Apache Software Foundation

TempoIQ

Initial release

2015

2014

2012

Current release

3.2.0, October 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

Server operating systems

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

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

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
ODBC

HTTP API

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

Java
Python
R
Scala

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

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.

User concepts

Access control

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

simple authentication-based access control

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