DBMS > Databend vs. Hazelcast vs. LevelDB vs. SAP HANA

System Properties Comparison Databend vs. Hazelcast vs. LevelDB vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

A widely adopted in-memory data grid

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

hazelcast.com

github.com/google/leveldb

www.sap.com/products/hana.html

Technical documentation

docs.databend.com

hazelcast.org/imdg/docs

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

help.sap.com/hana

Developer

Databend Labs

Hazelcast

Google

SAP

Initial release

2021

2008

2011

2010

Current release

1.0.59, April 2023

5.3.6, November 2023

1.23, February 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Rust

Java

C++

Server operating systems

hosted
Linux
macOS

All OS with a Java VM

Illumos
Linux
OS X
Windows

Appliance or cloud-service

Data scheme

yes

schema-free

yes

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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

SQLScript, R

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Replicated Map

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

Users with fine-grained authorization concept, user roles

Role-based access control

yes

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