DBMS > Apache Impala vs. Microsoft Azure AI Search vs. Redis vs. Trafodion

System Properties Comparison Apache Impala vs. Microsoft Azure AI Search vs. Redis vs. Trafodion

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

Search-as-a-service for web and mobile app development

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.

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Search engine

Key-value store

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

Relational DBMS

Secondary database models

Document store

Vector 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	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	5.75
Rank	#58	Overall
	#7	Search engines

Score	149.43
Rank	#6	Overall
	#1	Key-value stores

Website

impala.apache.org

azure.microsoft.com/en-us/services/search

redis.com
redis.io

trafodion.apache.org

Technical documentation

impala.apache.org/impala-docs.html

learn.microsoft.com/en-us/azure/search

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

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Microsoft

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Apache Software Foundation, originally developed by HP

Initial release

2013

2015

2009

2014

Current release

4.1.0, June 2022

7.2.5, May 2024

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

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

Open Source

Apache 2.0

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++

C++, Java

Server operating systems

Linux

hosted

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

with RediSearch module

yes

SQL

Support of SQL

SQL-like DML and DDL statements

with RediSQL module

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
JavaScript
Python

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

Java Stored Procedures

Triggers

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

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Implicit feature of the cloud service

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

through RedisGears

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual 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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

using Azure authentication

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.