DBMS > Amazon SimpleDB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Oracle vs. Sphinx

System Properties Comparison Amazon SimpleDB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Oracle vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

A widely adopted in-memory data grid

Fully managed big data interactive analytics platform

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

JSON support with IMDG 3.12

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
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	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

aws.amazon.com/simpledb

hazelcast.com

azure.microsoft.com/services/data-explorer

www.oracle.com/database

sphinxsearch.com

Technical documentation

docs.aws.amazon.com/simpledb

hazelcast.org/imdg/docs

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

docs.oracle.com/en/database

sphinxsearch.com/docs

Developer

Amazon

Hazelcast

Microsoft

Oracle

Sphinx Technologies Inc.

Initial release

2007

2008

2019

1980

2001

Current release

5.3.6, November 2023

cloud service with continuous releases

23c, September 2023

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses 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

Java

C and C++

C++

Server operating systems

hosted

All OS with a Java VM

hosted

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

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

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

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

All columns are indexed automatically

yes

all fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

Kusto Query Language (KQL), SQL subset

yes

with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Proprietary protocol

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

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

Event Listeners, Executor Services

Yes, possible languages: KQL, Python, R

PL/SQL

also stored procedures in Java possible

Triggers

yes

Events

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

Implicit feature of the cloud service

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

Replicated Map

yes

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

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

one or two-phase-commit; repeatable reads; read commited

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Role-based access control

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

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