DBMS > LevelDB vs. OrigoDB vs. PlanetScale vs. Transwarp StellarDB vs. XTDB

System Properties Comparison LevelDB vs. OrigoDB vs. PlanetScale vs. Transwarp StellarDB vs. XTDB

Editorial information provided by DB-Engines

Name

Description

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

A fully ACID in-memory object graph database

Scalable, distributed, serverless MySQL database platform built on top of Vitess

A distributed graph DBMS built for enterprise-level graph applications

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store

Document store
Object oriented DBMS

Relational DBMS

Graph DBMS

Document store

Secondary database models

Document store
Spatial DBMS

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

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

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

github.com/google/leveldb

origodb.com

planetscale.com

www.transwarp.cn/en/product/stellardb

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

origodb.com/docs

planetscale.com/docs

www.xtdb.com/docs

Developer

Google

Robert Friberg et al

PlanetScale

Transwarp

Juxt Ltd.

Initial release

2011

2009

under the name LiveDB

2020

2019

Current release

1.23, February 2021

1.19, September 2021

License

Commercial or Open Source

Open Source

BSD

Open Source

commercial

Open Source

MIT License

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++

Clojure

Server operating systems

Illumos
Linux
OS X
Windows

Linux
Windows

Docker
Linux
macOS

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

User defined using .NET types and collections

yes

yes, extensible-data-notation format

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

.NET Client API
HTTP API
LINQ

ADO.NET
JDBC
MySQL protocol
ODBC

OpenCypher

HTTP REST
JDBC

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Clojure
Java

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication
Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

depending on model

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

Write ahead log

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

Role based authorization

Users with fine-grained authorization concept

no user groups or roles

yes

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