DBMS > Coveo vs. Microsoft Azure Data Explorer vs. NCache vs. Oracle vs. Sphinx

System Properties Comparison Coveo vs. Microsoft Azure Data Explorer vs. NCache vs. Oracle vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

Fully managed big data interactive analytics platform

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

Widely used RDBMS

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

column oriented

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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	2.11
Rank	#118	Overall
	#11	Search engines

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

www.coveo.com

azure.microsoft.com/services/data-explorer

www.alachisoft.com/ncache

www.oracle.com/database

sphinxsearch.com

Technical documentation

docs.coveo.com

docs.microsoft.com/en-us/azure/data-explorer

www.alachisoft.com/resources/docs

docs.oracle.com/en/database

sphinxsearch.com/docs

Developer

Coveo

Microsoft

Alachisoft

Oracle

Sphinx Technologies Inc.

Initial release

2012

2019

2005

1980

2001

Current release

cloud service with continuous releases

5.3.3, April 2024

23c, September 2023

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

commercial

restricted free version is available

Open Source

GPL version 2, commercial licence 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

C#, .NET, .NET Core, Java

C and C++

C++

Server operating systems

hosted

Linux
Windows

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

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

Fixed schema with schema-less datatypes (dynamic)

schema-free

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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 fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

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

yes

with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Proprietary protocol

Supported programming languages

C#
Java
JavaScript
Python

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

.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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

support for stored procedures with SQL-Server CLR

PL/SQL

also stored procedures in Java possible

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Implicit feature of the cloud service

yes

Sharding, horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes, with selectable consistency level

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

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

yes

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

The original contents of fields are not stored in the Sphinx index.

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

granular access controls, API key management, content filters

Azure Active Directory Authentication

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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