DBMS > Coveo vs. Graph Engine vs. TimesTen vs. Warp 10

System Properties Comparison Coveo vs. Graph Engine vs. TimesTen vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Search engine

Graph DBMS
Key-value store

Relational DBMS

Time Series DBMS

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

Score	2.14
Rank	#116	Overall
	#11	Search engines

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

www.coveo.com

www.graphengine.io

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

www.warp10.io

Technical documentation

docs.coveo.com

www.graphengine.io/docs/manual

docs.oracle.com/en/database/other-databases/timesten/index.html

www.warp10.io/content/02_Getting_started

Developer

Coveo

Microsoft

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

SenX

Initial release

2012

2010

1998

2015

Current release

Release 22.1

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

Open Source

Apache License 2.0

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

.NET and C

Java

Server operating systems

hosted

.NET

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Linux
OS X
Windows

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

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

HTTP API
Jupyter
WebSocket

Supported programming languages

C#
Java
JavaScript
Python

C#
C++
F#
Visual Basic

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

PL/SQL

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

horizontal partitioning

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

by means of logfiles and checkpoints

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

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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