DBMS > Graphite vs. Oracle Berkeley DB vs. RocksDB vs. SurrealDB

System Properties Comparison Graphite vs. Oracle Berkeley DB vs. RocksDB vs. SurrealDB

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Editorial information provided by DB-Engines

Name

Description

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Widely used in-process key-value store

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

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

Document store
Graph DBMS

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

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

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

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

github.com/graphite-project/graphite-web

www.oracle.com/database/technologies/related/berkeleydb.html

rocksdb.org

surrealdb.com

Technical documentation

graphite.readthedocs.io

docs.oracle.com/cd/E17076_05/html/index.html

github.com/facebook/rocksdb/wiki

surrealdb.com/docs

Developer

Chris Davis

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Facebook, Inc.

SurrealDB Ltd

Initial release

2006

1994

2013

2022

Current release

18.1.40, May 2020

9.2.1, May 2024

v1.5.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial license available

Open Source

BSD

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Python

C, Java, C++ (depending on the Berkeley DB edition)

C++

Rust

Server operating systems

Linux
Unix

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

Numeric data only

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

SQL-like query language

APIs and other access methods

HTTP API
Sockets

C++ API
Java API

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

JavaScript (Node.js)
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

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

yes, based on authentication and database rules

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