DBMS > Apache Impala vs. Apache Phoenix vs. HarperDB vs. SQLite

System Properties Comparison Apache Impala vs. Apache Phoenix vs. HarperDB vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A scale-out RDBMS with evolutionary schema built on Apache HBase

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

phoenix.apache.org

docs.harperdb.io/docs

www.sqlite.org/docs.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

HarperDB

Dwayne Richard Hipp

Initial release

2013

2014

2017

2000

Current release

4.1.0, June 2022

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

3.1, August 2021

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

free community edition available

Open Source

Public Domain

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++

Java

Node.js

Server operating systems

Linux

Linux
Unix
Windows

Linux
OS X

server-less

Data scheme

yes

late-bound, schema-on-read capabilities

dynamic schema

yes

dynamic column types

Typing

predefined data types such as float or date

yes

JSON data types

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL-like data manipulation statements

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC

JDBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Custom Functions

since release 3.1

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

yes

the nodes on which a table resides can be defined

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

yes, using LMDB

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Access rights for users and roles

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