DBMS > Hypertable vs. NSDb vs. OrigoDB vs. RavenDB vs. Splunk

System Properties Comparison Hypertable vs. NSDb vs. OrigoDB vs. RavenDB vs. Splunk

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

An open source BigTable implementation based on distributed file systems such as Hadoop

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fully ACID in-memory object graph database

Open Source Operational and Transactional Enterprise NoSQL Document Database

Analytics Platform for Big Data

Primary database model

Wide column store

Time Series DBMS

Document store
Object oriented DBMS

Document store

Search engine

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	2.68
Rank	#102	Overall
	#19	Document stores

Score	93.02
Rank	#13	Overall
	#2	Search engines

Website

Technical documentation

nsdb.io/Architecture

origodb.com/docs

ravendb.net/docs

docs.splunk.com/Documentation/Splunk

Developer

Hypertable Inc.

Robert Friberg et al

Hibernating Rhinos

Splunk Inc.

Initial release

2009

2017

2009

under the name LiveDB

2010

2003

Current release

0.9.8.11, March 2016

5.4, July 2022

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

Apache Version 2.0

Open Source

AGPL version 3, commercial license available

commercial

Limited free edition and free developer edition 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++

Java, Scala

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
macOS

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

User defined using .NET types and collections

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.

can be achieved using .NET

yes

Secondary indexes

restricted

only exact value or prefix value scans

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language (RQL)

Splunk Search Processing Language for search commands

APIs and other access methods

C++ API
Thrift

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

.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

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

Java
Scala

.Net

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

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

Source-replica replication

Multi-source replication

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

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.

Eventual Consistency

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

Write ahead log

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

Role based authorization

Authorization levels configured per client per database

Access rights for users and roles

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