DBMS > Apache Druid vs. HarperDB vs. jBASE vs. Riak TS

System Properties Comparison Apache Druid vs. HarperDB vs. jBASE vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

A robust multi-value DBMS comprising development tools and middleware

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Relational DBMS
Time Series DBMS

Document store

Multivalue DBMS

Time Series DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	1.36
Rank	#157	Overall
	#3	Multivalue DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

druid.apache.org

www.harperdb.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

Technical documentation

druid.apache.org/docs/latest/design

docs.harperdb.io/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Apache Software Foundation and contributors

HarperDB

Rocket Software (formerly Zumasys)

Open Source, formerly Basho Technologies

Initial release

2012

2017

1991

2015

Current release

30.0.0, June 2024

3.1, August 2021

5.7

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free community edition available

commercial

Open Source

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

Node.js

Erlang

Server operating systems

Linux
OS X
Unix

Linux
OS X

AIX
Linux
Windows

Linux
OS X

Data scheme

yes

schema-less columns are supported

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

optional

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.

yes

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL for querying

SQL-like data manipulation statements

Embedded SQL for jBASE in BASIC

yes, limited

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

HTTP API
Native Erlang Interface

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
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

.Net
Basic
Jabbascript
Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

the nodes on which a table resides can be defined

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users and roles

Access rights can be defined down to the item level

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