DBMS > etcd vs. Oracle Berkeley DB vs. SAP HANA vs. Trino

System Properties Comparison etcd vs. Oracle Berkeley DB vs. SAP HANA vs. Trino

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Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Widely used in-process key-value store

In-memory, column based data store. Available as appliance or cloud service

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Website

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

www.oracle.com/database/technologies/related/berkeleydb.html

www.sap.com/products/hana.html

trino.io

Technical documentation

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

docs.oracle.com/cd/E17076_05/html/index.html

help.sap.com/hana

trino.io/broadcast
trino.io/docs/current

Social network pages

Developer

Oracle

originally developed by Sleepycat, which was acquired by Oracle

SAP

Trino Software Foundation

Initial release

1994

2010

2012

2020 rebranded from PrestoSQL

Current release

3.4, August 2019

18.1.40, May 2020

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial license available

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

C, Java, C++ (depending on the Berkeley DB edition)

Java

Server operating systems

FreeBSD
Linux
Windows

experimental

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Appliance or cloud-service

Linux
macOS

for devlopment

Data scheme

schema-free

yes

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

only with the Berkeley DB XML edition

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

gRPC
JSON over HTTP

JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

SQLScript, R

yes, depending on connected data-source

Triggers

yes, watching key changes

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

yes

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

depending on connected data-source

In-memory capabilities

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

yes

User concepts

Access control

yes

SQL standard access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenarios

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
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Key customers

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Market metrics

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Licensing and pricing models

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