DBMS > Amazon Redshift vs. Microsoft Azure Data Explorer vs. Quasardb vs. Redis vs. TigerGraph

System Properties Comparison Amazon Redshift vs. Microsoft Azure Data Explorer vs. Quasardb vs. Redis vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Fully managed big data interactive analytics platform

Distributed, high-performance timeseries database

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.

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS

column oriented

Time Series DBMS

Key-value store

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

Graph DBMS

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

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	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

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

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

aws.amazon.com/redshift

azure.microsoft.com/services/data-explorer

quasar.ai

redis.com
redis.io

www.tigergraph.com

Technical documentation

docs.aws.amazon.com/redshift

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

doc.quasar.ai/master

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

docs.tigergraph.com

Developer

Amazon (based on PostgreSQL)

Microsoft

quasardb

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2012

2019

2009

2017

Current release

cloud service with continuous releases

3.14.1, January 2024

7.2.5, May 2024

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

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

commercial

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++

Server operating systems

hosted

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

schema-free

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

integer and binary

partial

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

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

restricted

all fields are automatically indexed

yes

with tags

yes

with RediSearch module

SQL

Support of SQL

yes

does not fully support an SQL-standard

Kusto Query Language (KQL), SQL subset

SQL-like query language

with RediSQL module

SQL-like query language (GSQL)

APIs and other access methods

JDBC
ODBC

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

HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

C++
Java

Server-side scripts

Stored procedures

user defined functions

in Python

Yes, possible languages: KQL, Python, R

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

yes

Triggers

yes

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

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

Sharding

consistent hashing

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 with selectable replication factor

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

with Hadoop integration

through RedisGears

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

informational only, not enforced by the system

yes

Relationships in graphs

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts and optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Azure Active Directory Authentication

Cryptographically strong user authentication and audit trail

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

Role-based access control

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