DBMS > Apache Phoenix vs. InfluxDB vs. Redis vs. SingleStore vs. TerminusDB

System Properties Comparison Apache Phoenix vs. InfluxDB vs. Redis vs. SingleStore vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

DBMS for storing time series, events and metrics

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.

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Time Series DBMS

Key-value store

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

Relational DBMS

Graph DBMS

Secondary database models

Spatial DBMS

with GEO package

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

Document store
RDF store

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

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

Score	5.38
Rank	#62	Overall
	#35	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

phoenix.apache.org

www.influxdata.com/products/influxdb-overview

redis.com
redis.io

www.singlestore.com

terminusdb.com

Technical documentation

phoenix.apache.org

docs.influxdata.com/influxdb

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

docs.singlestore.com

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

SingleStore Inc.

DataChemist Ltd.

Initial release

2014

2013

2009

2013

2018

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

2.7.6, April 2024

7.2.5, May 2024

8.5, January 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

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

commercial

free developer edition available

Open Source

GPL V3

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Java

C++, Go

Prolog, Rust

Server operating systems

Linux
Unix
Windows

Linux
OS X

through Homebrew

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

64 bit version required

Linux

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

yes

SQL

Support of SQL

yes

SQL-like query language

with RediSQL module

yes

but no triggers and foreign keys

SQL-like query language (WOQL)

APIs and other access methods

JDBC

HTTP API
JSON over UDP

proprietary protocol

RESP - REdis Serialization Protocol

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
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

Bash
C
C#
Java
JavaScript (Node.js)
Python

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

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

yes

Triggers

publish/subscribe channels provide some trigger functionality; RedisGears

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

Sharding

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

Sharding

hash partitioning

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

in enterprise version only

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Source-replica replication

stores two copies of each physical data partition on two separate nodes

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

through RedisGears

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

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

ACID

Atomic execution of command blocks and scripts and optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

yes

in-memory journaling

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Depending on used storage engine

yes

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

simple rights management via user accounts

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

Fine grained access control via users, groups and roles

Role-based access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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F ree Tier and Enterprise Edition
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