DBMS > Badger vs. ClickHouse vs. Heroic vs. Microsoft Access vs. OpenTSDB

System Properties Comparison Badger vs. ClickHouse vs. Heroic vs. Microsoft Access vs. OpenTSDB

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in 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.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Scalable Time Series DBMS based on HBase

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.20
Rank	#325	Overall
	#49	Key-value stores

Score	16.20
Rank	#37	Overall
	#23	Relational DBMS

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Score	1.73
Rank	#147	Overall
	#12	Time Series DBMS

Website

github.com/dgraph-io/badger

clickhouse.com

github.com/spotify/heroic

www.microsoft.com/en-us/microsoft-365/access

opentsdb.net

Technical documentation

godoc.org/github.com/dgraph-io/badger

clickhouse.com/docs

spotify.github.io/heroic

developer.microsoft.com/en-us/access

opentsdb.net/docs/build/html/index.html

Developer

DGraph Labs

Clickhouse Inc.

Spotify

Microsoft

currently maintained by Yahoo and other contributors

Initial release

2017

2016

2014

1992

2011

Current release

v23.12.1.1368-stable, December 2023

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

Open Source

LGPL

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.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

C++

Java

C++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS

Windows

Not a real database server, but making use of DLLs

Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

via Elasticsearch

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

but not compliant to any SQL standard

APIs and other access methods

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
DAO
ODBC
OLE DB

HTTP API
Telnet 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#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

yes

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

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.

a simple user-level security was built in till version Access 2003

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