DBMS > etcd vs. eXtremeDB vs. Google Cloud Bigtable vs. Redis vs. RRDtool

System Properties Comparison etcd vs. eXtremeDB vs. Google Cloud Bigtable vs. Redis vs. RRDtool

Editorial information provided by DB-Engines

Name

Description

Natively in-memory DBMS with options for persistency, high-availability and clustering

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

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.

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Key-value store

Relational DBMS
Time Series DBMS

Key-value store
Wide column store

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

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

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

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

etcd.io
github.com/etcd-io/etcd

www.mcobject.com

cloud.google.com/bigtable

redis.com
redis.io

oss.oetiker.ch/rrdtool

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.mcobject.com/docs/extremedb.htm

cloud.google.com/bigtable/docs

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

oss.oetiker.ch/rrdtool/doc

Developer

McObject

Google

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Tobias Oetiker

Initial release

2001

2015

2009

1999

Current release

3.4, August 2019

8.2, 2021

7.2.4, January 2024

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

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

Open Source

GPL V2 and FLOSS

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.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Implementation language

C and C++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

FreeBSD
Linux
Windows

experimental

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

HP-UX
Linux

Data scheme

schema-free

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

Numeric data only

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.

support of XML interfaces available

Exporting into and restoring from XML files possible

Secondary indexes

yes

with RediSearch module

SQL

Support of SQL

yes

with the option: eXtremeSQL

with RediSQL module

APIs and other access methods

gRPC
JSON over HTTP

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

proprietary protocol

RESP - REdis Serialization Protocol

in-process shared library
Pipes

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
C
C#
C++
Java
Lua
Python
Scala

C#
C++
Go
Java
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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

yes

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

Triggers

yes, watching key changes

yes

by defining events

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Internal replication in Colossus, and regional replication between two clusters in different zones

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

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

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

Atomic execution of command blocks and scripts and optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

Data access is serialized by the server

yes

by using the rrdcached daemon

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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

Specific characteristics

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Competitive advantages

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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

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