DBMS > HEAVY.AI vs. Immudb vs. RocksDB vs. Rockset

System Properties Comparison HEAVY.AI vs. Immudb vs. RocksDB vs. Rockset

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Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

Key-value store

Document store

Secondary database models

Spatial DBMS

Relational DBMS

Relational DBMS
Search engine

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.31
Rank	#295	Overall
	#42	Key-value stores

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

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

github.com/heavyai/heavydb
www.heavy.ai

github.com/codenotary/immudb
immudb.io

rocksdb.org

rockset.com

Technical documentation

docs.heavy.ai

docs.immudb.io

github.com/facebook/rocksdb/wiki

docs.rockset.com

Developer

HEAVY.AI, Inc.

Codenotary

Facebook, Inc.

Rockset

Initial release

2016

2020

2013

2019

Current release

5.10, January 2022

1.2.3, April 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache Version 2.0

Open Source

BSD

commercial

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.

Implementation language

C++ and CUDA

C++

Server operating systems

Linux

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like syntax

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
ODBC
Thrift
Vega

gRPC protocol
PostgreSQL wire protocol

C++ API
Java API

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

.Net
Go
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

horizontal partitioning

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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