DBMS > Apache Impala vs. Badger vs. Cubrid vs. OrigoDB vs. Rockset

System Properties Comparison Apache Impala vs. Badger vs. Cubrid vs. OrigoDB vs. Rockset

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

A fully ACID in-memory object graph database

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

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Document store
Object oriented 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	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

impala.apache.org

github.com/dgraph-io/badger

cubrid.com (korean)
cubrid.org (english)

origodb.com

rockset.com

Technical documentation

impala.apache.org/impala-docs.html

godoc.org/github.com/dgraph-io/badger

cubrid.org/manuals

origodb.com/docs

docs.rockset.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

DGraph Labs

CUBRID Corporation, CUBRID Foundation

Robert Friberg et al

Rockset

Initial release

2013

2017

2008

2009

under the name LiveDB

2019

Current release

4.1.0, June 2022

11.0, January 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

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, C++, Java

C++

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

hosted

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like DML and DDL statements

yes

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

.NET Client API
HTTP API
LINQ

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Source-replica replication

yes

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

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

depending on model

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

Write ahead log

yes

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

Role based authorization

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

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

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