DBMS > Google BigQuery vs. Heroic vs. InfluxDB vs. SAP SQL Anywhere vs. TempoIQ

System Properties Comparison Google BigQuery vs. Heroic vs. InfluxDB vs. SAP SQL Anywhere vs. TempoIQ

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

DBMS for storing time series, events and metrics

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	26.56
Rank	#28	Overall
	#1	Time Series DBMS

Score	4.57
Rank	#78	Overall
	#43	Relational DBMS

Website

cloud.google.com/bigquery

github.com/spotify/heroic

www.influxdata.com/products/influxdb-overview

www.sap.com/products/technology-platform/sql-anywhere.html

tempoiq.com (offline)

Technical documentation

cloud.google.com/bigquery/docs

spotify.github.io/heroic

docs.influxdata.com/influxdb

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Google

Spotify

SAP

formerly Sybase

TempoIQ

Initial release

2010

2014

2013

1992

2012

Current release

2.7.5, January 2024

17, July 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

MIT-License; commercial enterprise version available

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

Server operating systems

hosted

Linux
OS X

through Homebrew

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

via Elasticsearch

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

RESTful HTTP/JSON API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API
JSON over UDP

ADO.NET
HTTP API
JDBC
ODBC

HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

in enterprise version only

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

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

Depending on used storage engine

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

simple rights management via user accounts

fine grained access rights according to SQL-standard

simple authentication-based access control

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