DBMS > Hyprcubd vs. LevelDB vs. OrigoDB vs. ScyllaDB vs. SQLite

System Properties Comparison Hyprcubd vs. LevelDB vs. OrigoDB vs. ScyllaDB vs. SQLite

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Serverless Time Series DBMS

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A fully ACID in-memory object graph database

Cassandra and DynamoDB compatible wide column store

Widely used embeddable, in-process RDBMS

Primary database model

Time Series DBMS

Key-value store

Document store
Object oriented DBMS

Wide column store

Relational DBMS

Secondary database models

Key-value store

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

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

hyprcubd.com (offline)

github.com/google/leveldb

origodb.com

www.scylladb.com

www.sqlite.org

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

origodb.com/docs

docs.scylladb.com

www.sqlite.org/docs.html

Developer

Hyprcubd, Inc.

Google

Robert Friberg et al

ScyllaDB

Dwayne Richard Hipp

Initial release

2011

2009

under the name LiveDB

2015

2000

Current release

1.23, February 2021

ScyllaDB Open Source 5.4.1, January 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

Open Source (AGPL), commercial license available

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

C++

Server operating systems

hosted

Illumos
Linux
OS X
Windows

Linux
Windows

Linux

server-less

Data scheme

yes

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

cluster global secondary indices

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements (CQL)

yes

SQL-92 is not fully supported

APIs and other access methods

gRPC (https)

.NET Client API
HTTP API
LINQ

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

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

yes, Lua

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

with automatic compression on writes

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

in-memory tables

yes

User concepts

Access control

token access

Role based authorization

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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