DBMS > GeoMesa vs. Redis vs. Riak TS vs. TDengine

System Properties Comparison GeoMesa vs. Redis vs. Riak TS vs. TDengine

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Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Time Series DBMS and big data platform

Primary database model

Spatial DBMS

Key-value store

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

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	0.78
Rank	#213	Overall
	#4	Spatial DBMS

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

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

www.geomesa.org

redis.com
redis.io

github.com/taosdata/TDengine
tdengine.com

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

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

www.tiot.jp/riak-docs/riak/ts/latest

docs.tdengine.com

Developer

CCRi and others

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Open Source, formerly Basho Technologies

TDEngine, previously Taos Data

Initial release

2014

2009

2015

2019

Current release

4.0.5, February 2024

7.2.4, January 2024

3.0.0, September 2022

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

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

Open Source

AGPL V3, also commercial editions available

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

Scala

Erlang

Server operating systems

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux
OS X

Linux
Windows

Data scheme

yes

schema-free

yes

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

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.

Secondary indexes

yes

with RediSearch module

restricted

SQL

Support of SQL

with RediSQL module

yes, limited

Standard SQL with extensions for time-series applications

APIs and other access methods

proprietary protocol

RESP - REdis Serialization Protocol

HTTP API
Native Erlang Interface

JDBC
RESTful HTTP API

Supported programming languages

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

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

Server-side scripts

Stored procedures

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

Erlang

Triggers

publish/subscribe channels provide some trigger functionality; RedisGears

yes

pre-commit hooks and post-commit hooks

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

through RedisGears

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

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

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

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

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

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

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

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