DBMS > Heroic vs. LevelDB vs. OrientDB vs. XTDB

System Properties Comparison Heroic vs. LevelDB vs. OrientDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Multi-model DBMS (Document, Graph, Key/Value)

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

Primary database model

Time Series DBMS

Key-value store

Document store
Graph DBMS
Key-value store

Document store

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

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

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

github.com/spotify/heroic

github.com/google/leveldb

orientdb.org

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

Technical documentation

spotify.github.io/heroic

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

www.orientdb.com/docs/last/index.html

www.xtdb.com/docs

Developer

Spotify

Google

OrientDB LTD; CallidusCloud; SAP

Juxt Ltd.

Initial release

2014

2011

2010

2019

Current release

1.23, February 2021

3.2.29, March 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

Open Source

Apache version 2

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++

Java

Clojure

Server operating systems

Illumos
Linux
OS X
Windows

All OS with a Java JDK (>= JDK 6)

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

Data scheme

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language, no joins

limited SQL, making use of Apache Calcite

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Clojure
Java

Server-side scripts

Stored procedures

Java, Javascript

Triggers

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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.

User concepts

Access control

Access rights for users and roles; record level security configurable

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
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