DBMS > Apache Druid vs. H2 vs. HarperDB vs. InfluxDB vs. SQLite

System Properties Comparison Apache Druid vs. H2 vs. HarperDB vs. InfluxDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

DBMS for storing time series, events and metrics

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

druid.apache.org

www.h2database.com

www.harperdb.io

www.influxdata.com/products/influxdb-overview

www.sqlite.org

Technical documentation

druid.apache.org/docs/latest/design

www.h2database.com/html/main.html

docs.harperdb.io/docs

docs.influxdata.com/influxdb

www.sqlite.org/docs.html

Developer

Apache Software Foundation and contributors

Thomas Mueller

HarperDB

Dwayne Richard Hipp

Initial release

2012

2005

2017

2013

2000

Current release

29.0.1, April 2024

2.2.220, July 2023

3.1, August 2021

2.7.6, April 2024

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

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

commercial

free community edition available

Open Source

MIT-License; commercial enterprise version available

Open Source

Public Domain

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

Node.js

Server operating systems

Linux
OS X
Unix

All OS with a Java VM

Linux
OS X

through Homebrew

server-less

Data scheme

yes

schema-less columns are supported

yes

dynamic schema

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

JSON data types

Numeric data and Strings

yes

not rigid because of 'dynamic typing' concept.

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

SQL for querying

yes

SQL-like data manipulation statements

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

HTTP API
JSON over UDP

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java

.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

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Custom Functions

since release 3.1

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

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

Sharding

in enterprise version only

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

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

yes

the nodes on which a table resides can be defined

selectable replication factor

in enterprise version only

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

Durability

Support for making data persistent

yes

yes, using LMDB

yes

In-memory capabilities

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

yes

Depending on used storage engine

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

Access rights for users and roles

simple rights management via user accounts

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