DBMS > Google Cloud Datastore vs. Hypertable vs. Manticore Search vs. MySQL vs. NuoDB

System Properties Comparison Google Cloud Datastore vs. Hypertable vs. Manticore Search vs. MySQL vs. NuoDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Widely used open source RDBMS

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

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	4.36
Rank	#72	Overall
	#12	Document stores

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Website

cloud.google.com/datastore

manticoresearch.com

www.mysql.com

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

cloud.google.com/datastore/docs

manual.manticoresearch.com

dev.mysql.com/doc

doc.nuodb.com

Developer

Google

Hypertable Inc.

Manticore Software

Oracle

since 2010, originally MySQL AB, then Sun

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2008

2009

2017

1995

2013

Current release

0.9.8.11, March 2016

6.0, February 2023

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

Open Source

GPL version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

limited edition free

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

C and C++

C++

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

schema-free

Fixed schema

yes

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

Secondary indexes

yes

restricted

only exact value or prefix value scans

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

C++ API
Thrift

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

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC

Supported programming languages

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

C++
Java
Perl
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

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

Server-side scripts

Stored procedures

using Google App Engine

user defined functions

yes

proprietary syntax

Java, SQL

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

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

selectable replication factor on file system level

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

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

not for MyISAM storage engine

yes

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

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

MVCC

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

Temporary table

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

Standard SQL roles/ privileges, Administrative Users

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