DBMS > Amazon CloudSearch vs. BigObject vs. etcd vs. Newts vs. Oracle

System Properties Comparison Amazon CloudSearch vs. BigObject vs. etcd vs. Newts vs. Oracle

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

Analytic DBMS for real-time computations and queries

A distributed reliable key-value store

Time Series DBMS based on Cassandra

Widely used RDBMS

Primary database model

Search engine

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Time Series DBMS

Relational DBMS

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	1.81
Rank	#137	Overall
	#12	Search engines

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

aws.amazon.com/cloudsearch

bigobject.io

etcd.io
github.com/etcd-io/etcd

opennms.github.io/newts

www.oracle.com/database

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.bigobject.io

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

github.com/OpenNMS/newts/wiki

docs.oracle.com/en/database

Developer

Amazon

BigObject, Inc.

OpenNMS Group

Oracle

Initial release

2012

2015

2014

1980

Current release

3.4, August 2019

23c, September 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

restricted free version is 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

C and C++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
Windows

experimental

Linux
OS X
Windows

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

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

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

all search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

HTTP API

fluentd
ODBC
RESTful HTTP API

gRPC
JSON over HTTP

HTTP REST
Java API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Java

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

Server-side scripts

Stored procedures

Lua

PL/SQL

also stored procedures in Java possible

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

none

Sharding

based on Cassandra

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

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

User concepts

Access control

authentication via encrypted signatures

fine grained access rights according to SQL-standard

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