DBMS > Amazon CloudSearch vs. HarperDB vs. Heroic vs. NCache vs. Oracle

System Properties Comparison Amazon CloudSearch vs. HarperDB vs. Heroic vs. NCache vs. Oracle

Editorial information provided by DB-Engines

Name

Description

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Open-Source and Enterprise in-memory Key-Value Store

Widely used RDBMS

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

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	1.85
Rank	#137	Overall
	#12	Search engines

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

aws.amazon.com/cloudsearch

www.harperdb.io

github.com/spotify/heroic

www.alachisoft.com/ncache

www.oracle.com/database

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.harperdb.io/docs

spotify.github.io/heroic

www.alachisoft.com/resources/docs

docs.oracle.com/en/database

Developer

Amazon

HarperDB

Spotify

Alachisoft

Oracle

Initial release

2012

2017

2014

2005

1980

Current release

3.1, August 2021

5.3.3, April 2024

23c, September 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Enterprise Edition available

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

Node.js

Java

C#, .NET, .NET Core, Java

C and C++

Server operating systems

hosted

Linux
OS X

Linux
Windows

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

Data scheme

yes

dynamic schema

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

JSON data types

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like data manipulation statements

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

with proprietary extensions

APIs and other access methods

HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

HQL (Heroic Query Language, a JSON-based language)
HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

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

Custom Functions

since release 3.1

support for stored procedures with SQL-Server CLR

PL/SQL

also stored procedures in Java possible

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

A table resides as a whole on one (or more) nodes in a cluster

Sharding

yes

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

the nodes on which a table resides can be defined

yes

yes, with selectable consistency level

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

optimistic locking and pessimistic locking

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

Access rights for users and roles

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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