DBMS > Apache Druid vs. HarperDB vs. RocksDB vs. STSdb vs. Warp 10

System Properties Comparison Apache Druid vs. HarperDB vs. RocksDB vs. STSdb vs. Warp 10

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

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.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS
Time Series DBMS

Document store

Key-value store

Time Series DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

druid.apache.org

www.harperdb.io

rocksdb.org

github.com/STSSoft/STSdb4

www.warp10.io

Technical documentation

druid.apache.org/docs/latest/design

docs.harperdb.io/docs

github.com/facebook/rocksdb/wiki

www.warp10.io/content/02_Getting_started

Developer

Apache Software Foundation and contributors

HarperDB

Facebook, Inc.

STS Soft SC

SenX

Initial release

2012

2017

2013

2011

2015

Current release

29.0.1, April 2024

3.1, August 2021

9.2.1, May 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free community edition available

Open Source

BSD

Open Source

GPLv2, commercial license available

Open Source

Apache License 2.0

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

C++

Java

Server operating systems

Linux
OS X
Unix

Linux
OS X

Linux

Windows

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

dynamic schema

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

yes

primitive types and user defined types (classes)

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 for querying

SQL-like data manipulation statements

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

C++ API
Java API

.NET Client API

HTTP API
Jupyter
WebSocket

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

C
C++
Go
Java
Perl
Python
Ruby

C#
Java

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

WarpScript

Triggers

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

horizontal partitioning

none

Sharding

based on HBase

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

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

yes

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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