DBMS > Atos Standard Common Repository vs. ClickHouse vs. Elasticsearch vs. HarperDB vs. Lovefield

System Properties Comparison Atos Standard Common Repository vs. ClickHouse vs. Elasticsearch vs. HarperDB vs. Lovefield

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Document store
Key-value store

Secondary database models

Time Series DBMS

Document store
Spatial DBMS
Vector DBMS

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

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	128.79
Rank	#8	Overall
	#1	Search engines

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

clickhouse.com

www.elastic.co/elasticsearch

www.harperdb.io

google.github.io/lovefield

Technical documentation

clickhouse.com/docs

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

docs.harperdb.io/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Atos Convergence Creators

Clickhouse Inc.

Elastic

HarperDB

Google

Initial release

2016

2010

2017

2014

Current release

1703

v24.6.2.17-stable, July 2024

8.6, January 2023

3.1, August 2021

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Elastic License

commercial

free community edition available

Open Source

Apache 2.0

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.

ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

Java

C++

Java

Node.js

JavaScript

Server operating systems

Linux

FreeBSD
Linux
macOS

All OS with a Java VM

Linux
OS X

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

dynamic schema

yes

Typing

predefined data types such as float or date

optional

yes

JSON data types

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

SQL-like data manipulation statements

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

LDAP

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

Java API
RESTful HTTP/JSON API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Supported programming languages

All languages with LDAP bindings

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

JavaScript

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

Triggers

yes

by using the 'percolation' feature

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

key based and custom

Sharding

A table resides as a whole on one (or more) nodes in a cluster

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes

the nodes on which a table resides can be defined

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

Memcached and Redis integration

yes

using MemoryDB

User concepts

Access control

LDAP bind authentication

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Access rights for users and roles

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