DBMS > Heroic vs. LevelDB vs. Teradata vs. XTDB vs. YottaDB

System Properties Comparison Heroic vs. LevelDB vs. Teradata vs. XTDB vs. YottaDB

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

A hybrid cloud data analytics software platform (Teradata Vantage)

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

A fast and solid embedded Key-value store

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

Relational DBMS

using the Octo plugin

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

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

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

github.com/spotify/heroic

github.com/google/leveldb

www.teradata.com

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

yottadb.com

Technical documentation

spotify.github.io/heroic

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

docs.teradata.com

www.xtdb.com/docs

yottadb.com/resources/documentation

Developer

Spotify

Google

Teradata

Juxt Ltd.

YottaDB, LLC

Initial release

2014

2011

1984

2019

2001

Current release

1.23, February 2021

Teradata Vantage 1.0 MU2, January 2019

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

commercial

Open Source

MIT License

Open Source

AGPL 3.0

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++

Clojure

Server operating systems

Illumos
Linux
OS X
Windows

hosted
Linux

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

Docker
Linux

Data scheme

schema-free

yes

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

yes

SQL

Support of SQL

yes

SQL 2016 + extensions

limited SQL, making use of Apache Calcite

by using the Octo plugin

APIs and other access methods

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

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

HTTP REST
JDBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Clojure
Java

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

yes, each node contains all data

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

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

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

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

More information provided by the system vendor

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More resources

DB-Engines blog posts

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