DBMS > Firebase Realtime Database vs. QuestDB vs. Redis vs. Solr vs. Vertica

System Properties Comparison Firebase Realtime Database vs. QuestDB vs. Redis vs. Solr vs. Vertica

Editorial information provided by DB-Engines

Name

Description

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

A high performance open source SQL database for time series data

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 widely used distributed, scalable search engine based on Apache Lucene

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Document store

Time Series DBMS

Key-value store

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

Search engine

Relational DBMS

Column oriented

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

Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	2.70
Rank	#105	Overall
	#8	Time Series DBMS

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

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

firebase.google.com/products/realtime-database

Technical documentation

firebase.google.com/docs/database

questdb.io/docs

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

solr.apache.org/resources.html

vertica.com/documentation

Developer

Google

acquired by Google 2014

QuestDB Technology Inc

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Apache Software Foundation

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2012

2014

2009

2006

2005

Current release

7.2.5, May 2024

9.6.0, April 2024

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

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

Open Source

Apache Version 2

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

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

Java (Zero-GC), C++, Rust

Java

C++

Server operating systems

hosted

Linux
macOS
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Data scheme

schema-free

yes

schema-free via InfluxDB Line Protocol

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

supports customizable data types and automatic typing

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

All search fields are automatically indexed

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL with time-series extensions

with RediSQL module

Solr Parallel SQL Interface

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

proprietary protocol

RESP - REdis Serialization Protocol

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Java
JavaScript
Objective-C

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

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
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

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

Java plugins

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

Callbacks are triggered when data changes

publish/subscribe channels provide some trigger functionality; RedisGears

yes

User configurable commands triggered on index changes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by timestamps)

Sharding

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

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with eventual consistency

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

through RedisGears

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID for single-table writes

Atomic execution of command blocks and scripts and optimistic locking

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

through memory mapped files

yes

User concepts

Access control

yes, based on authentication and database rules

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

yes

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

Cost-based models and subscription-based models are both available. One license is...
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News

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23 May 2024

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8 May 2024

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6 May 2024

Does "vpmovzxbd" Scare You? Here's Why it Doesn't Have To
12 April 2024

Create an ADS-B flight radar with QuestDB and a Raspberry Pi
8 April 2024

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