DBMS > HBase vs. JSqlDb vs. Microsoft SQL Server vs. NCache vs. Redis

System Properties Comparison HBase vs. JSqlDb vs. Microsoft SQL Server vs. NCache vs. Redis

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

JavaScript Query Language Database, stores JavaScript objects and primitives

Microsofts flagship relational DBMS

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.

Primary database model

Wide column store

Document store
Object oriented DBMS

Relational 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
Graph DBMS
Spatial DBMS

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

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

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

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

Website

hbase.apache.org

jsqldb.org (offline)

www.microsoft.com/en-us/sql-server

www.alachisoft.com/ncache

redis.com
redis.io

Technical documentation

hbase.apache.org/book.html

learn.microsoft.com/en-US/sql/sql-server

www.alachisoft.com/resources/docs

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Konrad von Backstrom

Microsoft

Alachisoft

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2008

2018

1989

2005

2009

Current release

2.3.4, January 2021

0.8, December 2018

SQL Server 2022, November 2022

5.3.3, April 2024

7.2.4, January 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

commercial

restricted free version is available

Open Source

Enterprise Edition available

Open Source

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

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

C#, .NET, .NET Core, Java

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux
macOS
Windows

Linux
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

schema-free, schema definition possible

schema-free

yes

schema-free

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

partial

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

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

Secondary indexes

yes

with RediSearch module

SQL

Support of SQL

yes

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

with RediSQL module

APIs and other access methods

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

IDistributedCache
JCache
LINQ
Proprietary native API

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

JavaScript

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.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

Server-side scripts

Stored procedures

yes

Coprocessors in Java

functions in JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

support for stored procedures with SQL-Server CLR

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

Triggers

yes

Notifications

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes, but depending on the SQL-Server Edition

yes, with selectable consistency level

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

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

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

Single row ACID (across millions of columns)

ACID

optimistic locking and pessimistic locking

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

using RocksDB

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

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