DBMS > Apache Impala vs. Machbase Neo vs. Realm vs. WakandaDB

System Properties Comparison Apache Impala vs. Machbase Neo vs. Realm vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

TimeSeries DBMS for AIoT and BigData

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

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	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

machbase.com/dbms

realm.io/docs

wakanda.github.io/doc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Machbase

Realm, acquired by MongoDB in May 2019

Wakanda SAS

Initial release

2013

2014

2012

Current release

4.1.0, June 2022

V8.0, August 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free test version available

Open Source

AGPLv3, extended commercial license available

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++

C++, JavaScript

Server operating systems

Linux

Linux
macOS
Windows

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
Java

with Android only
Objective-C
React Native
Swift

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

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

Foreign keys

Referential integrity

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.

yes

volatile and lookup table

yes

In-Memory realm

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

simple password-based access control

yes

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More resources

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Recent citations in the news

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