DBMS > Firebolt vs. Manticore Search vs. Postgres-XL vs. Redis

System Properties Comparison Firebolt vs. Manticore Search vs. Postgres-XL vs. Redis

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Multi-storage database for search, including full-text search.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

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

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial 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	1.49
Rank	#148	Overall
	#68	Relational DBMS

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

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

Website

Technical documentation

docs.firebolt.io

manual.manticoresearch.com

www.postgres-xl.org/documentation

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

Developer

Firebolt Analytics Inc.

Manticore Software

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2020

2017

2014

since 2012, originally named StormDB

2009

Current release

6.0, February 2023

10 R1, October 2018

7.2.5, May 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

Mozilla public license

Open Source

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

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++

Server operating systems

hosted

FreeBSD
Linux
macOS
Windows

Linux
macOS

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

yes

Fixed schema

yes

schema-free

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

yes

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.

Can index from XML

yes

XML type, but no XML query functionality

Secondary indexes

yes

full-text index on all search fields

yes

with RediSearch module

SQL

Support of SQL

yes

SQL-like query language

yes

distributed, parallel query execution

with RediSQL module

APIs and other access methods

.Net
ODBC
RESTful HTTP API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

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

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

Go
JavaScript (Node.js)
Python

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

user defined functions

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

Triggers

yes

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Synchronous replication based on Galera library

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

MVCC

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

The original contents of fields are not stored in the Manticore index.

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

fine grained access rights according to SQL-standard

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

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.