DBMS > CrateDB vs. LevelDB vs. RocksDB vs. TinkerGraph

System Properties Comparison CrateDB vs. LevelDB vs. RocksDB vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

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

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

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Key-value store

Graph DBMS

Secondary database models

Relational DBMS

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

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#10	Vector DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

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

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

cratedb.com

github.com/google/leveldb

rocksdb.org

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

cratedb.com/docs

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

github.com/facebook/rocksdb/wiki

Developer

Crate

Google

Facebook, Inc.

Initial release

2013

2011

2013

2009

Current release

1.23, February 2021

9.2.1, May 2024

License

Commercial or Open Source

Open Source

BSD

Open Source

BSD

Open Source

Apache 2.0

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

Java

C++

Java

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Illumos
Linux
OS X
Windows

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

C++ API
Java API

TinkerPop 3

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Go
Java
Perl
Python
Ruby

Groovy
Java

Server-side scripts

Stored procedures

user defined functions (Javascript)

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

optional

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

rights management via user accounts

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