DBMS > Apache Impala vs. Brytlyt vs. JaguarDB vs. Oracle NoSQL

System Properties Comparison Apache Impala vs. Brytlyt vs. JaguarDB vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Performant, highly scalable DBMS for AI and IoT applications

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Document store
Key-value store
Relational DBMS

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	0.38
Rank	#276	Overall
	#127	Relational DBMS

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

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Website

impala.apache.org

brytlyt.io

www.jaguardb.com

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

impala.apache.org/impala-docs.html

docs.brytlyt.io

www.jaguardb.com/support.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Brytlyt

DataJaguar, Inc.

Oracle

Initial release

2013

2016

2015

2011

Current release

4.1.0, June 2022

5.0, August 2023

3.3 July 2023

24.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

GPL V3.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C, C++ and CUDA

C++

the server part. Clients available in other languages

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux

Linux
Solaris SPARC/x86

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

in PL/pgSQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

Multi-source replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

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.

yes

off heap cache

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

rights management via user accounts

Access rights for users and roles

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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

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Brytlyt releases version 5.0, introducing a more intuitive, intelligent and flexible analytics platform
1 August 2023, PR Newswire

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22 December 2021, Silicon Canals

Brytlyt Secures $4M in Series A Funding
20 May 2020, Datanami

Bringing GPUs To Bear On Bog Standard Relational Databases
26 February 2018, The Next Platform

Brytlyt raises £3.8m for '1000x faster analytics'
22 December 2021, BusinessCloud

provided by Google News

Oracle Beefs Up Its NoSQL Database Offering
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OpenWorld 2013: Oracle NoSQL Database On the Rise?
13 December 2023, Channel Futures

Blog Theme - Details
21 August 2023, blogs.oracle.com

We built a geo-distributed, serverless modern app using the Oracle NoSQL Database Cloud Service
18 November 2021, blogs.oracle.com

Oracle NoSQL database comes to the cloud
2 April 2020, TechTarget

provided by Google News

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