DBMS > ITTIA vs. Redis vs. searchxml vs. Spark SQL

System Properties Comparison ITTIA vs. Redis vs. searchxml vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

Edge Time Series DBMS with Real-Time Stream Processing

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.

DBMS for structured and unstructured content wrapped with an application server

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Time Series DBMS

Key-value store

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

Native XML DBMS
Search engine

Relational DBMS

Secondary database models

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	0.44
Rank	#267	Overall
	#23	Time Series DBMS

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

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

www.ittia.com

redis.com
redis.io

www.searchxml.net/category/products

spark.apache.org/sql

Technical documentation

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

www.searchxml.net/support/handouts

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

ITTIA L.L.C.

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

informationpartners gmbh

Apache Software Foundation

Initial release

2007

2009

2015

2014

Current release

8.7

7.2.5, May 2024

1.0

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

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

commercial

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 and C++

C++

Scala

Server operating systems

Linux
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Windows

Linux
OS X
Windows

Data scheme

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

yes

with RediSearch module

yes

SQL

Support of SQL

yes

with RediSQL module

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC
RESTful HTTP API
WebSocket

proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP API
WebDAV
XQuery
XSLT

JDBC
ODBC

Supported programming languages

C
C++
JavaScript (Node.js)
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

C++

most other programming languages supported via APIs

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

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

yes

on the application server

Triggers

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

yes

sychronisation to multiple collections

none

MapReduce

Offers an API for user-defined Map/Reduce methods

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

Atomic execution of command blocks and scripts and optimistic locking

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

Database file passwords

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

Domain, group and role-based access control at the document level and for application services

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