DBMS > Apache Impala vs. Infobright vs. RavenDB vs. XTDB

System Properties Comparison Apache Impala vs. Infobright vs. RavenDB vs. XTDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Primary database model

Relational DBMS

Document store

Secondary database models

Document store

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

impala.apache.org

ignitetech.com/softwarelibrary/infobrightdb

ravendb.net

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

Technical documentation

impala.apache.org/impala-docs.html

ravendb.net/docs

www.xtdb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Ignite Technologies Inc.; formerly InfoBright Inc.

Hibernating Rhinos

Juxt Ltd.

Initial release

2013

2005

2010

2019

Current release

4.1.0, June 2022

5.4, July 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

AGPL version 3, commercial license available

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++

Clojure

Server operating systems

Linux

Linux
Windows

Linux
macOS
Raspberry Pi
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

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language (RQL)

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

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

Multi-source replication

yes, each node contains all data

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

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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

exploiting MySQL or PostgreSQL frontend capabilities

Authorization levels configured per client per database

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

RavenDB Launches Version 6.0 Lightning Fast Queries, Data Integrations, Corax Indexing Engine, and Sharding
3 October 2023, PR Newswire

Install the NoSQL RavenDB Data System
14 May 2021, The New Stack

RavenDB Adds Graph Queries
15 May 2019, Datanami

Review: NoSQL database RavenDB
20 March 2019, TechGenix

RavenDB Welcomes David Baruc as Chief Revenue Officer: Seasoned Tech Leader to Drive Global Sales and ...
13 June 2023, PR Newswire

provided by Google News

Share this page