DBMS > Alibaba Cloud Table Store vs. Dgraph vs. Hive vs. Microsoft Azure Data Explorer vs. Newts

System Properties Comparison Alibaba Cloud Table Store vs. Dgraph vs. Hive vs. Microsoft Azure Data Explorer vs. Newts

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Distributed and scalable native Graph DBMS

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Fully managed big data interactive analytics platform

Time Series DBMS based on Cassandra

Primary database model

column oriented

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	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

www.alibabacloud.com/product/table-store

dgraph.io

hive.apache.org

azure.microsoft.com/services/data-explorer

opennms.github.io/newts

Technical documentation

www.alibabacloud.com/help/en/tablestore

dgraph.io/docs

cwiki.apache.org/confluence/display/Hive/Home

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

github.com/OpenNMS/newts/wiki

Developer

Alibaba

Dgraph Labs, Inc.

Apache Software Foundation

initially developed by Facebook

Microsoft

OpenNMS Group

Initial release

2016

2012

2019

2014

Current release

3.1.3, April 2022

cloud service with continuous releases

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2

commercial

Open Source

Apache 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

Java

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

Fixed schema with schema-less datatypes (dynamic)

schema-free

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

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

SQL

Support of SQL

SQL-like DML and DDL statements

Kusto Query Language (KQL), SQL subset

APIs and other access methods

HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JDBC
ODBC
Thrift

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

HTTP REST
Java API

Supported programming languages

Java
Python

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

C++
Java
PHP
Python

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

Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Yes, possible languages: KQL, Python, R

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Synchronous replication via Raft

selectable replication factor

yes

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

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Access rights based on subaccounts and tokens

Planned for future releases

Access rights for users, groups and roles

Azure Active Directory Authentication

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

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

Apache Software Foundation Announces New Top-Level Project Apache® Paimon
16 April 2024, GlobeNewswire

Gartner’s Magic Quadrant for Cloud Database Management Systems
9 December 2020, CRN

Top data analytics tools comparison: Alibaba Cloud, AWS, Azure, Google Cloud, IBM
5 December 2019, Wire19

Apache Software Foundation Announces New Top-Level Project Apache Paimon
19 April 2024, Datanami

provided by Google News

Dgraph on AWS: Setting up a horizontally scalable graph database | Amazon Web Services
1 September 2020, AWS Blog

Dgraph Rises to the Top Graph Database on GitHub With 11 G2 Badges and 11M Downloads
26 May 2021, Business Wire

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

Dgraph launches Slash GraphQL, a GraphQL-native database Backend-as-a-Service
10 September 2020, TechCrunch

provided by Google News

Apache Software Foundation Announces Apache Hive 4.0
30 April 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

GC Tuning for Improved Presto Reliability
11 January 2024, Uber

provided by Google News

We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates
31 May 2024, Microsoft

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, Microsoft

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

Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services
7 February 2019, Microsoft

provided by Google News

Share this page