DBMS > CrateDB vs. OpenEdge vs. SQLite vs. Trino

System Properties Comparison CrateDB vs. OpenEdge vs. SQLite vs. Trino

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

Application development environment with integrated database management system

Widely used embeddable, in-process RDBMS

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

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational 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	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Website

cratedb.com

www.progress.com/openedge

www.sqlite.org

trino.io

Technical documentation

cratedb.com/docs

documentation.progress.com/output/ua/OpenEdge_latest

www.sqlite.org/docs.html

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

Developer

Crate

Progress Software Corporation

Dwayne Richard Hipp

Trino Software Foundation

Initial release

2013

1984

2000

2012

2020 rebranded from PrestoSQL

Current release

5.8.1, August 2024

OpenEdge 12.2, March 2020

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

Open Source

commercial

Open Source

Public Domain

Open Source

Apache Version 2.0

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

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

AIX
HP-UX
Linux
Solaris
Windows

server-less

Linux
macOS

for devlopment

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

depending on connected data-source

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

close to SQL 92

yes

SQL-92 is not fully supported

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

Progress proprietary ABL (Advanced Business Language)

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

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

since Version 11.4

none

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Source-replica replication

none

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

Eventual Consistency
Read-after-write consistency on record level

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

rights management via user accounts

Users and groups

SQL standard access control

More information provided by the system vendor

News

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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