DBMS > H2 vs. LevelDB vs. OrigoDB vs. Spark SQL vs. XTDB

System Properties Comparison H2 vs. LevelDB vs. OrigoDB vs. Spark SQL vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

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

Primary database model

Relational DBMS

Key-value store

Document store
Object oriented DBMS

Relational DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

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

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

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.h2database.com

github.com/google/leveldb

origodb.com

spark.apache.org/sql

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

Technical documentation

www.h2database.com/html/main.html

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

origodb.com/docs

spark.apache.org/docs/latest/sql-programming-guide.html

www.xtdb.com/docs

Developer

Thomas Mueller

Google

Robert Friberg et al

Apache Software Foundation

Juxt Ltd.

Initial release

2005

2011

2009

under the name LiveDB

2014

2019

Current release

2.2.220, July 2023

1.23, February 2021

3.5.0 ( 2.13), September 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

BSD

Open Source

Apache 2.0

Open Source

MIT License

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++

Scala

Clojure

Server operating systems

All OS with a Java VM

Illumos
Linux
OS X
Windows

Linux
Windows

Linux
OS X
Windows

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

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

SQL-like DML and DDL statements

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

.NET Client API
HTTP API
LINQ

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net

Java
Python
R
Scala

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

none

Source-replica replication

none

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

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Role based authorization

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