DBMS > Apache Impala vs. EsgynDB vs. JaguarDB vs. Rockset

System Properties Comparison Apache Impala vs. EsgynDB vs. JaguarDB vs. Rockset

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Performant, highly scalable DBMS for AI and IoT applications

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Document store

Secondary database models

Document store

Relational DBMS
Search engine

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

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

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

Technical documentation

impala.apache.org/impala-docs.html

www.jaguardb.com/support.html

docs.rockset.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Esgyn

DataJaguar, Inc.

Rockset

Initial release

2013

2015

2019

Current release

4.1.0, June 2022

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

GPL V3.0

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++

C++, Java

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like DML and DDL statements

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

JDBC
ODBC

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication between multi datacenters

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual 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

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

fine grained access rights according to SQL-standard

rights management via user accounts

Access rights for users and organizations can be defined via Rockset console

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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

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

provided by Google News

Rockset upgrades database to meet the needs of AI hybrid search – Blocks and Files
20 May 2024, Blocks and Files

Rockset launches native support for hybrid vector and text search to power AI apps
16 May 2024, SiliconANGLE News

Rockset Announces Native Support for Hybrid Search to Power AI Apps
17 May 2024, Datanami

Data Management News for the Week of May 17; Updates from Anomalo, DataStax, Rockset & More
16 May 2024, Solutions Review

Rockset targets cost control with latest database update
31 January 2024, TechTarget

provided by Google News

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