DBMS > atoti vs. Google BigQuery vs. Google Cloud Spanner vs. Graphite vs. SAP IQ

System Properties Comparison atoti vs. Google BigQuery vs. Google Cloud Spanner vs. Graphite vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Large scale data warehouse service with append-only tables

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.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Columnar RDBMS optimized for Big Data analytics

Primary database model

column-oriented

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

Score	0.45
Rank	#253	Overall
	#13	Object oriented DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	5.19
Rank	#62	Overall
	#4	Time Series DBMS

Score	2.56
Rank	#106	Overall
	#52	Relational DBMS

Website

atoti.io

cloud.google.com/bigquery

cloud.google.com/spanner

github.com/graphite-project/graphite-web

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

docs.atoti.io

cloud.google.com/bigquery/docs

cloud.google.com/spanner/docs

graphite.readthedocs.io

help.sap.com/docs/SAP_IQ

Developer

ActiveViam

Google

Chris Davis

SAP, formerly Sybase

Initial release

2010

2017

2006

1994

Current release

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

free versions available

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Python

Server operating systems

hosted

Linux
Unix

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Multidimensional Expressions (MDX)

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

RESTful HTTP/JSON API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP API
Sockets

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Python

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Sharding

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

none

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

Since BigQuery is designed for querying data

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

locking

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)

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

fine grained access rights according to SQL-standard

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