DBMS > AgensGraph vs. BoltDB vs. Databricks vs. RocksDB

System Properties Comparison AgensGraph vs. BoltDB vs. Databricks vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

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

Primary database model

Graph DBMS
Relational DBMS

Key-value store

Document store
Relational DBMS

Key-value store

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

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

Website

bitnine.net/agensgraph

github.com/boltdb/bolt

www.databricks.com

rocksdb.org

Technical documentation

bitnine.net/documentation

docs.databricks.com

github.com/facebook/rocksdb/wiki

Developer

Bitnine Global Inc.

Databricks

Facebook, Inc.

Initial release

2016

2013

Current release

2.1, December 2018

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

MIT License

commercial

Open Source

BSD

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++

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Solaris
Windows

hosted

Linux

Data scheme

depending on used data model

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

yes

with Databricks SQL

APIs and other access methods

Cypher Query Language
JDBC

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

C
Java
JavaScript
Python

Python
R
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

Triggers

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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