DBMS > RocksDB vs. Sadas Engine vs. Vertica

System Properties Comparison RocksDB vs. Sadas Engine vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Key-value store

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

rocksdb.org

www.sadasengine.com

www.vertica.com

Technical documentation

github.com/facebook/rocksdb/wiki

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

vertica.com/documentation

Developer

Facebook, Inc.

SADAS s.r.l.

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2013

2006

2005

Current release

8.11.4, April 2024

8.0

12.0.3, January 2023

License

Commercial or Open Source

Open Source

BSD

commercial

free trial version available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

Linux

AIX
Linux
Windows

Linux

Data scheme

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

C++ API
Java API

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

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Competitive advantages

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Key customers

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Licensing and pricing models

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