DBMS > BoltDB vs. ClickHouse vs. Elasticsearch vs. GraphDB

System Properties Comparison BoltDB vs. ClickHouse vs. Elasticsearch vs. GraphDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Primary database model

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	0.76
Rank	#224	Overall
	#32	Key-value stores

Score	16.20
Rank	#37	Overall
	#23	Relational DBMS

Score	134.78
Rank	#7	Overall
	#1	Search engines

Score	3.10
Rank	#100	Overall
	#7	Graph DBMS
	#4	RDF stores

Website

github.com/boltdb/bolt

clickhouse.com

www.elastic.co/elasticsearch

www.ontotext.com

Technical documentation

clickhouse.com/docs

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

graphdb.ontotext.com/documentation

Social network pages

Developer

Clickhouse Inc.

Elastic

Ontotext

Initial release

2013

2016

2010

2000

Current release

v24.3.2.23-lts, April 2024

8.6, January 2023

10.4, October 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Elastic License

commercial

Some plugins of GraphDB Workbench are open sourced

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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
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.

Implementation language

C++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS

All OS with a Java VM

All OS with a Java VM
Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

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

schema-free and OWL/RDFS-schema support; RDF shapes

Typing

predefined data types such as float or date

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

All search fields are automatically indexed

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

APIs and other access methods

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

Java API
RESTful HTTP/JSON API

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

Supported programming languages

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#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

well-defined plugin interfaces; JavaScript server-side extensibility

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

none

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, Eventual consistency (configurable in cluster mode per master or individual client request)

Foreign keys

Referential integrity

yes

Constraint checking

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Memcached and Redis integration

User concepts

Access control

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.

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

Scaling Understanding with the Help of Feedback Loops, Knowledge Graphs and NLP
19 April 2024

How Knowledge Graphs Power Data Mesh and Data Fabric
10 April 2024

Building Smarter Financial Services: The Role of Semantic Technologies, Knowledge Graphs and Generative AI
3 April 2024

Using GraphDB’s Natural Language Interface to Talk with Your Content
29 March 2024

Choosing A Graph Data Model to Best Serve Your Use Case
27 March 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.