DBMS > Coveo vs. LeanXcale vs. Percona Server for MongoDB vs. Postgres-XL vs. TempoIQ

System Properties Comparison Coveo vs. LeanXcale vs. Percona Server for MongoDB vs. Postgres-XL vs. TempoIQ

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It 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 highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Search engine

Key-value store
Relational DBMS

Document store

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.28
Rank	#114	Overall
	#11	Search engines

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

www.coveo.com

www.leanxcale.com

www.percona.com/mongodb/software/percona-server-for-mongodb

www.postgres-xl.org

tempoiq.com (offline)

Technical documentation

docs.coveo.com

docs.percona.com/percona-distribution-for-mongodb

www.postgres-xl.org/documentation

Developer

Coveo

LeanXcale

Percona

TempoIQ

Initial release

2012

2015

2014

since 2012, originally named StormDB

2012

Current release

3.4.10-2.10, November 2017

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

GPL Version 2

Open Source

Mozilla public license

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.

Implementation language

C++

Server operating systems

hosted

Linux

Linux
macOS

Data scheme

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

yes

schema-free

yes

schema-free

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

proprietary protocol using JSON

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP API

Supported programming languages

C#
Java
JavaScript
Python

C
Java
Scala

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

JavaScript

user defined functions

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

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

via In-Memory Engine

User concepts

Access control

granular access controls, API key management, content filters

Access rights for users and roles

fine grained access rights according to SQL-standard

simple authentication-based access control

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