DBMS > Apache Impala vs. NCache vs. Oracle Rdb vs. Redis vs. TimescaleDB

System Properties Comparison Apache Impala vs. NCache vs. Oracle Rdb vs. Redis vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

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 time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

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

Time Series DBMS

Secondary database models

Document store

Document store
Search engine

Using distributed Lucene

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

Relational DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

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

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	155.94
Rank	#6	Overall
	#1	Key-value stores

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

impala.apache.org

www.alachisoft.com/ncache

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

redis.com
redis.io

www.timescale.com

Technical documentation

impala.apache.org/impala-docs.html

www.alachisoft.com/resources/docs

www.oracle.com/database/technologies/related/rdb-doc.html

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

docs.timescale.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Alachisoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Timescale

Initial release

2013

2005

1984

2009

2017

Current release

4.1.0, June 2022

5.3.3, April 2024

7.4.1.1, 2021

7.2.5, May 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Enterprise Edition available

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

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++

C#, .NET, .NET Core, Java

Server operating systems

Linux

Linux
Windows

HP Open VMS

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux
OS X
Windows

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

yes

partial

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

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

with RediSearch module

yes

SQL

Support of SQL

SQL-like DML and DDL statements

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

yes

with RediSQL module

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
ODBC

IDistributedCache
JCache
LINQ
Proprietary native API

proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

All languages supporting JDBC/ODBC

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

support for stored procedures with SQL-Server CLR

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

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Notifications

publish/subscribe channels provide some trigger functionality; RedisGears

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

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

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, with selectable consistency level

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

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

optimistic locking and pessimistic locking

yes, on a single node

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

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

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

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

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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