DBMS > etcd vs. H2 vs. HarperDB vs. Microsoft Access vs. SQLite

System Properties Comparison etcd vs. H2 vs. HarperDB vs. Microsoft Access vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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.

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.)

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Spatial DBMS

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Trend Chart

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

etcd.io
github.com/etcd-io/etcd

www.h2database.com

www.harperdb.io

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

www.sqlite.org

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.h2database.com/html/main.html

docs.harperdb.io/docs

developer.microsoft.com/en-us/access

www.sqlite.org/docs.html

Developer

Thomas Mueller

HarperDB

Microsoft

Dwayne Richard Hipp

Initial release

2005

2017

1992

2000

Current release

3.4, August 2019

2.2.220, July 2023

3.1, August 2021

1902 (16.0.11328.20222), March 2019

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

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

commercial

free community edition available

commercial

Bundled with Microsoft Office

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

C++

Server operating systems

FreeBSD
Linux
Windows

experimental

All OS with a Java VM

Linux
OS X

Windows

Not a real database server, but making use of DLLs

server-less

Data scheme

schema-free

yes

dynamic schema

yes

dynamic column types

Typing

predefined data types such as float or date

yes

JSON data types

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

yes

SQL-like data manipulation statements

yes

but not compliant to any SQL standard

yes

SQL-92 is not fully supported

APIs and other access methods

gRPC
JSON over HTTP

JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
DAO
ODBC
OLE DB

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

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

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

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

yes

since Access 2010 using the ACE-engine

Triggers

yes, watching key changes

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

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

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

but no files for transaction logging

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

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

fine grained access rights according to SQL-standard

Access rights for users and roles

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

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