DBMS > Google Cloud Datastore vs. HBase vs. Lovefield vs. Oracle NoSQL vs. Sadas Engine

System Properties Comparison Google Cloud Datastore vs. HBase vs. Lovefield vs. Oracle NoSQL vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

Embeddable relational database for web apps written in pure JavaScript

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

Primary database model

Document store

Wide column store

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

cloud.google.com/datastore

hbase.apache.org

google.github.io/lovefield

www.oracle.com/database/nosql/technologies/nosql

www.sadasengine.com

Technical documentation

cloud.google.com/datastore/docs

hbase.apache.org/book.html

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.oracle.com/en/database/other-databases/nosql-database/index.html

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

Developer

Google

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Google

Oracle

SADAS s.r.l.

Initial release

2008

2014

2011

2006

Current release

2.3.4, January 2021

2.1.12, February 2017

23.3, December 2023

8.0

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

free trial version 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

Java

JavaScript

Java

C++

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Solaris SPARC/x86

AIX
Linux
Windows

Data scheme

schema-free

schema-free, schema definition possible

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes, details here

options to bring your own types, AVRO

yes

optional

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

SQL-like query language (GQL)

SQL-like query language

via JavaScript builder pattern

SQL-like DML and DDL statements

yes

APIs and other access methods

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

Java API
RESTful HTTP API
Thrift

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

JavaScript

C
C#
Go
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

using Google App Engine

yes

Coprocessors in Java

Triggers

Callbacks using the Google Apps Engine

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

Multi-source replication
Source-replica replication

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

with Hadoop integration

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 or Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

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

Single row ACID (across millions of columns)

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

off heap cache

yes

managed by 'Learn by Usage'

User concepts

Access control

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Access rights for users and roles

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

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Related products and services

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