DBMS > Graph Engine vs. GridDB vs. Microsoft Azure AI Search vs. Postgres-XL vs. TempoIQ

System Properties Comparison Graph Engine vs. GridDB vs. Microsoft Azure AI Search 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

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

Scalable in-memory time series database optimized for IoT and Big Data

Search-as-a-service for web and mobile app development

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

Graph DBMS
Key-value store

Secondary database models

Key-value store
Relational DBMS

Vector DBMS

Document store
Spatial DBMS

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

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

www.graphengine.io

griddb.net

azure.microsoft.com/en-us/services/search

www.postgres-xl.org

tempoiq.com (offline)

Technical documentation

www.graphengine.io/docs/manual

docs.griddb.net

learn.microsoft.com/en-us/azure/search

www.postgres-xl.org/documentation

Developer

Microsoft

Toshiba Corporation

Microsoft

TempoIQ

Initial release

2010

2013

2015

2014

since 2012, originally named StormDB

2012

Current release

5.1, August 2022

10 R1, October 2018

License

Commercial or Open Source

Open Source

MIT License

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

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

.NET and C

C++

Server operating systems

.NET

Linux

hosted

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL92, SQL-like TQL (Toshiba Query Language)

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

RESTful HTTP API

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

HTTP API

Supported programming languages

C#
C++
F#
Visual Basic

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C#
Java
JavaScript
Python

.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

yes

user defined functions

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID at container level

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

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

Access rights for users can be defined per database

yes

using Azure authentication

fine grained access rights according to SQL-standard

simple authentication-based access control

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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.

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