DBMS > Google Cloud Datastore vs. Manticore Search vs. MySQL vs. Teradata Aster

System Properties Comparison Google Cloud Datastore vs. Manticore Search vs. MySQL vs. Teradata Aster

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

Multi-storage database for search, including full-text search.

Widely used open source RDBMS

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store

Search engine

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

cloud.google.com/datastore

manticoresearch.com

www.mysql.com

Technical documentation

cloud.google.com/datastore/docs

manual.manticoresearch.com

dev.mysql.com/doc

Developer

Google

Manticore Software

Oracle

since 2010, originally MySQL AB, then Sun

Teradata

Initial release

2008

2017

1995

2005

Current release

6.0, February 2023

8.3.0, January 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are 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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C++

C and C++

Server operating systems

hosted

FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

Fixed schema

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes, details here

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

yes

in Aster File Store

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language (GQL)

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

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

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

using Google App Engine

user defined functions

yes

proprietary syntax

R packages

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

SQL Map-Reduce Framework

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

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

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

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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