DBMS > Google Cloud Datastore vs. OpenTSDB vs. Oracle vs. Realm vs. TimesTen

System Properties Comparison Google Cloud Datastore vs. OpenTSDB vs. Oracle vs. Realm vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

Scalable Time Series DBMS based on HBase

Widely used RDBMS

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

cloud.google.com/datastore

opentsdb.net

www.oracle.com/database

realm.io

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

cloud.google.com/datastore/docs

opentsdb.net/docs/build/html/index.html

docs.oracle.com/en/database

realm.io/docs

docs.oracle.com/database/timesten-18.1

Developer

Google

currently maintained by Yahoo and other contributors

Oracle

Realm, acquired by MongoDB in May 2019

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2008

2011

1980

2014

1998

Current release

23c, September 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

LGPL

commercial

restricted free version is available

Open Source

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

C and C++

Server operating systems

hosted

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Android
Backend: server-less
iOS
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes, details here

numeric data for metrics, strings for tags

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

SQL

Support of SQL

SQL-like query language (GQL)

yes

with proprietary extensions

yes

APIs and other access methods

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

HTTP API
Telnet API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

Erlang
Go
Java
Python
R
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

using Google App Engine

PL/SQL

also stored procedures in Java possible

runs within the applications so server-side scripts are unnecessary

PL/SQL

Triggers

Callbacks using the Google Apps Engine

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

selectable replication factor

based on HBase

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

can be realized in PL/SQL

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

based on HBase

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

In-Memory realm

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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