DBMS > Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. PostGIS vs. Redis

System Properties Comparison Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. PostGIS vs. Redis

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Editorial information provided by DB-Engines

Name

Description

Fully managed big data interactive analytics platform

Widely used in-process key-value store

Spatial extension of PostgreSQL

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

Primary database model

Relational DBMS

column oriented

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Spatial DBMS

Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

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

Relational DBMS

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

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

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	157.80
Rank	#6	Overall
	#1	Key-value stores

Website

azure.microsoft.com/services/data-explorer

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

postgis.net

redis.com
redis.io

Technical documentation

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

docs.oracle.com/cd/E17076_05/html/index.html

postgis.net/documentation

docs.redis.com/latest/index.html
redis.io/docs

Developer

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2019

1994

2005

2009

Current release

cloud service with continuous releases

18.1.40, May 2020

3.4.2, February 2024

7.2.4, January 2024

License

Commercial or Open Source

commercial

Open Source

commercial license available

Open Source

GPL v2.0

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

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.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Implementation language

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

Fixed schema with schema-less datatypes (dynamic)

schema-free

yes

schema-free

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

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

only with the Berkeley DB XML edition

yes

Secondary indexes

all fields are automatically indexed

yes

with RediSearch module

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

yes

SQL interfaced based on SQLite is available

yes

with RediSQL module

APIs and other access methods

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

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

user defined functions

Lua; Redis Functions coming in Redis 7 (slides and Github)

Triggers

yes

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

yes

only for the SQL API

yes

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

yes

based on PostgreSQL

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

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.

Source-replica replication

yes

based on PostgreSQL

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

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

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts and optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities

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

yes

User concepts

Access control

Azure Active Directory Authentication

yes

based on PostgreSQL

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

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