DBMS > HEAVY.AI vs. LevelDB vs. searchxml vs. TempoIQ

System Properties Comparison HEAVY.AI vs. LevelDB vs. searchxml vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

DBMS for structured and unstructured content wrapped with an application server

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

Primary database model

Relational DBMS

Key-value store

Native XML DBMS
Search engine

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

github.com/heavyai/heavydb
www.heavy.ai

github.com/google/leveldb

www.searchxml.net/category/products

tempoiq.com (offline)

Technical documentation

docs.heavy.ai

github.com/google/leveldb/blob/main/doc/index.md

www.searchxml.net/support/handouts

Developer

HEAVY.AI, Inc.

Google

informationpartners gmbh

TempoIQ

Initial release

2016

2011

2015

2012

Current release

5.10, January 2022

1.23, February 2021

1.0

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

BSD

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++ and CUDA

C++

Server operating systems

Linux

Illumos
Linux
OS X
Windows

Windows

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC
Thrift
Vega

RESTful HTTP API
WebDAV
XQuery
XSLT

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C++

most other programming languages supported via APIs

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

on the application server

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

simple authentication-based access control

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