DBMS > GBase vs. Lovefield vs. Microsoft Azure Data Explorer vs. Quasardb vs. TimesTen

System Properties Comparison GBase vs. Lovefield vs. Microsoft Azure Data Explorer vs. Quasardb vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Embeddable relational database for web apps written in pure JavaScript

Fully managed big data interactive analytics platform

Distributed, high-performance timeseries database

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

column oriented

Time Series DBMS

Relational DBMS

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.gbase.cn

google.github.io/lovefield

azure.microsoft.com/services/data-explorer

quasar.ai

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

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.microsoft.com/en-us/azure/data-explorer

doc.quasar.ai/master

docs.oracle.com/database/timesten-18.1

Developer

General Data Technology Co., Ltd.

Google

Microsoft

quasardb

Oracle, TimesTen Performance Software, HP

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

Initial release

2004

2014

2019

2009

1998

Current release

GBase 8a, GBase 8s, GBase 8c

2.1.12, February 2017

cloud service with continuous releases

3.14.1, January 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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, Java, Python

JavaScript

C++

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

BSD
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

schema-free

yes

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

yes

integer and binary

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

all fields are automatically indexed

yes

with tags

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

via JavaScript builder pattern

Kusto Query Language (KQL), SQL subset

SQL-like query language

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

JavaScript

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

Yes, possible languages: KQL, Python, R

PL/SQL

Triggers

yes

Using read-only observers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication with selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

by using LevelDB

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

Transient mode

yes

User concepts

Access control

yes

Azure Active Directory Authentication

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, azure.microsoft.com

Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog
13 July 2023, Microsoft

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, azure.microsoft.com

Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services
7 February 2019, azure.microsoft.com

Log and Telemetry Analytics Performance Benchmark
16 August 2022, Gigaom

provided by Google News

Record quasar is most luminous object in the universe
20 February 2024, EarthSky

Quasar Partners with PTC to Empower IoT Customers with High-Performance Data Solutions
11 September 2023, Datanami

QUASAR yacht (Bilgin, 46.8m, 2016)
3 July 2023, Boat International

Quasar Selected by National Renewable Energy Laboratory to Help with Energy System De-risking and Optimization
6 June 2023, PR Newswire

Meet the NiceGUI: Your Soon-to-be Favorite Python UI Library
16 April 2024, Towards Data Science

provided by Google News

Share this page