DBMS > Google Cloud Datastore vs. Sadas Engine vs. Teradata vs. WakandaDB

System Properties Comparison Google Cloud Datastore vs. Sadas Engine vs. Teradata vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A hybrid cloud data analytics software platform (Teradata Vantage)

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store

Relational DBMS

Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

cloud.google.com/datastore

www.sadasengine.com

www.teradata.com

wakanda.github.io

Technical documentation

cloud.google.com/datastore/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.teradata.com

wakanda.github.io/doc

Developer

Google

SADAS s.r.l.

Teradata

Wakanda SAS

Initial release

2008

2006

1984

2012

Current release

8.0

Teradata Vantage 1.0 MU2, January 2019

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

AGPLv3, extended commercial license available

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

C++

C++, JavaScript

Server operating systems

hosted

AIX
Linux
Windows

hosted
Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes, details here

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL-like query language (GQL)

yes

SQL 2016 + extensions

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

JavaScript

Server-side scripts

Stored procedures

using Google App Engine

yes

UDFs, stored procedures, table functions in parallel

yes

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

managed by 'Learn by Usage'

yes

User concepts

Access control

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

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

yes

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More resources

DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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