DBMS > Apache Impala vs. JaguarDB vs. Microsoft Azure SQL Database vs. XTDB

System Properties Comparison Apache Impala vs. JaguarDB vs. Microsoft Azure SQL Database vs. XTDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Performant, highly scalable DBMS for AI and IoT applications

Database as a Service offering with high compatibility to Microsoft SQL Server

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Document store

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#15	Vector DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

impala.apache.org

www.jaguardb.com

azure.microsoft.com/en-us/products/azure-sql/database

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

impala.apache.org/impala-docs.html

www.jaguardb.com/support.html

docs.microsoft.com/en-us/azure/azure-sql

www.xtdb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

DataJaguar, Inc.

Microsoft

Juxt Ltd.

Initial release

2013

2015

2010

2019

Current release

4.1.0, June 2022

3.3 July 2023

V12

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPL V3.0

commercial

Open Source

MIT License

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++

the server part. Clients available in other languages

C++

Clojure

Server operating systems

Linux

hosted

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

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

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

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

yes, with always 3 replicas available

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 for users, groups and roles

based on Apache Sentry and Kerberos

rights management via user accounts

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

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2020
4 January 2021, Paul Andlinger, Matthias Gelbmann

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

show all

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Copilot in Azure SQL Database in Private Preview
27 March 2024, InfoQ.com

Microsoft unveils Copilot for Azure SQL Database
27 March 2024, InfoWorld

Azure SQL Database migration to OCI - resources estimation and migration approach
11 January 2024, blogs.oracle.com

Expand the limits of innovation with Azure data
21 March 2024, microsoft.com

Why migrate Windows Server and SQL Server to Azure: ROI, innovation, and free offers
25 April 2024, microsoft.com

provided by Google News

Share this page