DBMS > Google BigQuery vs. Graph Engine vs. HEAVY.AI vs. LevelDB vs. TempoIQ

System Properties Comparison Google BigQuery vs. Graph Engine vs. HEAVY.AI vs. LevelDB vs. TempoIQ

Editorial information provided by DB-Engines

Name

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

Description

Large scale data warehouse service with append-only tables

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

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

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

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Key-value store

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Website

cloud.google.com/bigquery

www.graphengine.io

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

github.com/google/leveldb

tempoiq.com (offline)

Technical documentation

cloud.google.com/bigquery/docs

www.graphengine.io/docs/manual

docs.heavy.ai

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

Developer

Google

Microsoft

HEAVY.AI, Inc.

Google

TempoIQ

Initial release

2010

2016

2011

2012

Current release

5.10, January 2022

1.23, February 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

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

.NET and C

C++ and CUDA

C++

Server operating systems

hosted

.NET

Linux

Illumos
Linux
OS X
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.

Secondary indexes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API

JDBC
ODBC
Thrift
Vega

HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
F#
Visual Basic

All languages supporting JDBC/ODBC/Thrift
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

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

Since BigQuery is designed for querying data

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

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

simple authentication-based access control

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