DBMS > Apache Impala vs. MaxDB vs. Qdrant vs. XTDB

System Properties Comparison Apache Impala vs. MaxDB vs. Qdrant vs. XTDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A robust and reliable RDBMS optimized to run all major SAP solutions

A high-performance vector database with neural network or semantic-based matching

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

Primary database model

Relational DBMS

Vector DBMS

Document store

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	1.28
Rank	#167	Overall
	#8	Vector DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

impala.apache.org

maxdb.sap.com

github.com/qdrant/qdrant
qdrant.tech

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

Technical documentation

impala.apache.org/impala-docs.html

maxdb.sap.com/documentation

qdrant.tech/documentation

www.xtdb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

SAP, acquired from Software AG (Adabas-D) in 1997

Qdrant

Juxt Ltd.

Initial release

2013

1984

2021

2019

Current release

4.1.0, June 2022

7.9.10.12, February 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Limited community edition free

Open Source

Apache Version 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Rust

Clojure

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows

Docker
Linux
macOS
Windows

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

Numbers, Strings, Geo, Boolean

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.

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
WebDAV

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C#
Java
Perl
PHP
Python

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

Collection-level replication

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

Eventual Consistency, tunable 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.

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Key-based 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

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

SAP Content Server High Availability using Amazon EFS and SUSE | Amazon Web Services
30 December 2020, AWS Blog

Extended Maintenance Commitments Across SAP Solutions
11 August 2020, SAP News

What is SAP S/4HANA?
21 March 2022, TechTarget

IBM Cloud SAP-Certified Infrastructure Features
22 January 2019, ibm.com

Alibaba Cloud Offers Access to SAP Software for Customers
5 June 2018, Alizila

provided by Google News

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Qdrant Raises $28M to Advance Massive-Scale AI Applications
23 January 2024, businesswire.com

Qdrant Hybrid Cloud is Now Available for OCI Customers: Managed Vector Search Engine for Data-Sensitive AI ...
16 April 2024, blogs.oracle.com

Qdrant offers managed vector database for hybrid clouds
16 April 2024, InfoWorld

Why Vector Data Services For AI Are A Moveable Feast
17 April 2024, Forbes

provided by Google News

Share this page