DBMS > Coveo vs. LMDB vs. MySQL vs. OpenEdge vs. Teradata Aster

System Properties Comparison Coveo vs. LMDB vs. MySQL vs. OpenEdge vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

A high performant, light-weight, embedded key-value database library

Widely used open source RDBMS

Application development environment with integrated database management system

Platform for big data analytics on multistructured data sources and types

Primary database model

Search engine

Key-value store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Website

www.coveo.com

www.symas.com/symas-embedded-database-lmdb

www.mysql.com

www.progress.com/openedge

Technical documentation

docs.coveo.com

www.lmdb.tech/doc

dev.mysql.com/doc

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Coveo

Symas

Oracle

since 2010, originally MySQL AB, then Sun

Progress Software Corporation

Teradata

Initial release

2012

2011

1995

1984

2005

Current release

0.9.32, January 2024

8.4.0, April 2024

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C and C++

Server operating systems

hosted

Linux
Unix
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

schema-free

yes

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

close to SQL 92

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C#
Java
JavaScript
Python

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Progress proprietary ABL (Advanced Business Language)

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

since Version 11.4

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

Source-replica replication

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

yes

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

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

granular access controls, API key management, content filters

Users with fine-grained authorization concept

no user groups or roles

Users and groups

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.