DBMS > Couchbase vs. Hawkular Metrics vs. InfluxDB vs. Memgraph vs. Sadas Engine

System Properties Comparison Couchbase vs. Hawkular Metrics vs. InfluxDB vs. Memgraph vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

DBMS for storing time series, events and metrics

An open source graph database built for real-time streaming and compatible with Neo4j

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Spatial DBMS

with GEO package

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	3.19
Rank	#94	Overall
	#8	Graph DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

www.couchbase.com

www.hawkular.org

www.influxdata.com/products/influxdb-overview

memgraph.com

www.sadasengine.com

Technical documentation

docs.couchbase.com

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.influxdata.com/influxdb

memgraph.com/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Social network pages

Developer

Couchbase, Inc.

Community supported by Red Hat

Memgraph Ltd

SADAS s.r.l.

Initial release

2011

2014

2013

2017

2006

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

2.7.6, April 2024

8.0

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

BSL 1.1; commercial license for enterprise edition available

commercial

free trial version 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.

Implementation language

C, C++, Go and Erlang

Java

C and C++

C++

Server operating systems

Linux
OS X
Windows

Linux
OS X

through Homebrew

Linux

AIX
Linux
Windows

Data scheme

schema-free

schema-free and schema-optional

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like query language

yes

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

HTTP REST

HTTP API
JSON over UDP

Bolt protocol
Cypher query language

JDBC
ODBC
Proprietary protocol

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Go
Java
Python
Ruby

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

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Triggers

yes

via the TAP protocol

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

based on Cassandra

Sharding

in enterprise version only

Sharding

dynamic graph partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

selectable replication factor

based on Cassandra

selectable replication factor

in enterprise version only

Multi-source replication using RAFT

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

Depending on used storage engine

yes

managed by 'Learn by Usage'

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

simple rights management via user accounts

Users, roles and permissions

Access rights for users, groups and roles according to SQL-standard

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

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
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Licensing and pricing models

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You can check out our pricing model and licenses on the company website .
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