DBMS > Badger vs. Databend vs. InfinityDB vs. RocksDB

System Properties Comparison Badger vs. Databend vs. InfinityDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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 Java embedded Key-Value Store which extends the Java Map interface

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

Primary database model

Key-value store

Relational DBMS

Key-value store

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

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

Website

github.com/dgraph-io/badger

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

boilerbay.com

rocksdb.org

Technical documentation

godoc.org/github.com/dgraph-io/badger

docs.databend.com

boilerbay.com/infinitydb/manual

github.com/facebook/rocksdb/wiki

Developer

DGraph Labs

Databend Labs

Boiler Bay Inc.

Facebook, Inc.

Initial release

2017

2021

2002

2013

Current release

1.0.59, April 2023

4.0

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

Open Source

BSD

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

Rust

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted
Linux
macOS

All OS with a Java VM

Linux

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

C++ API
Java API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

yes

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

Users with fine-grained authorization concept, user roles

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