DBMS > BoltDB vs. ClickHouse vs. Drizzle vs. GridGain vs. OrientDB

System Properties Comparison BoltDB vs. ClickHouse vs. Drizzle vs. GridGain vs. OrientDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

An embedded key-value store for Go.

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.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

GridGain is an in-memory computing platform, built on Apache Ignite

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Key-value store

Relational DBMS

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store

Secondary database models

Time Series DBMS

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Website

github.com/boltdb/bolt

clickhouse.com

www.gridgain.com

orientdb.org

Technical documentation

clickhouse.com/docs

www.gridgain.com/docs/index.html

www.orientdb.com/docs/last/index.html

Developer

Clickhouse Inc.

Drizzle project, originally started by Brian Aker

GridGain Systems, Inc.

OrientDB LTD; CallidusCloud; SAP

Initial release

2013

2016

2008

2007

2010

Current release

v24.4.1.2088-stable, May 2024

7.2.4, September 2012

GridGain 8.5.1

3.2.29, March 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

GNU GPL

commercial

Open Source

Apache version 2

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.

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Implementation language

C++

Java, C++, .Net

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS

FreeBSD
Linux
OS X

Linux
OS X
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

with proprietary extensions

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language, no joins

APIs and other access methods

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

JDBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

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

C
C++
Java
PHP

C#
C++
Java
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

yes

yes (compute grid and cache interceptors can be used instead)

Java, Javascript

Triggers

hooks for callbacks inside the server can be used.

yes (cache interceptors and events)

Hooks

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Multi-source replication
Source-replica replication

yes (replicated cache)

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

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

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.

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Security Hooks for custom implementations

Access rights for users and roles; record level security configurable

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