DBMS > atoti vs. Couchbase vs. H2 vs. InfluxDB vs. LevelDB

System Properties Comparison atoti vs. Couchbase vs. H2 vs. InfluxDB vs. LevelDB

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

DBMS for storing time series, events and metrics

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Website

atoti.io

www.couchbase.com

www.h2database.com

www.influxdata.com/products/influxdb-overview

github.com/google/leveldb

Technical documentation

docs.atoti.io

docs.couchbase.com

www.h2database.com/html/main.html

docs.influxdata.com/influxdb

github.com/google/leveldb/blob/main/doc/index.md

Developer

ActiveViam

Couchbase, Inc.

Thomas Mueller

Google

Initial release

2011

2005

2013

2011

Current release

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

2.2.220, July 2023

2.7.6, April 2024

1.23, February 2021

License

Commercial or Open Source

commercial

free versions available

Open Source

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

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

MIT-License; commercial enterprise version available

Open Source

BSD

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

Java

C, C++, Go and Erlang

Java

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux
OS X

through Homebrew

Illumos
Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

Multidimensional Expressions (MDX)

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

yes

SQL-like query language

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

JDBC
ODBC

HTTP API
JSON over UDP

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Server-side scripts

Stored procedures

Python

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

Java Stored Procedures and User-Defined Functions

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Automatic Sharding

none

Sharding

in enterprise version only

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

selectable replication factor

in enterprise version only

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

simple rights management via user accounts

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