DBMS > Heroic vs. RocksDB vs. Teradata Aster vs. TinkerGraph

System Properties Comparison Heroic vs. RocksDB vs. Teradata Aster vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

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

Platform for big data analytics on multistructured data sources and types

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

Primary database model

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

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

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

github.com/spotify/heroic

rocksdb.org

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

Technical documentation

spotify.github.io/heroic

github.com/facebook/rocksdb/wiki

Developer

Spotify

Facebook, Inc.

Teradata

Initial release

2014

2013

2005

2009

Current release

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

commercial

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

Linux

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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.

yes

in Aster File Store

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

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

C++ API
Java API

ADO.NET
JDBC
ODBC
OLE DB

TinkerPop 3

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Java
Python
R

Groovy
Java

Server-side scripts

Stored procedures

R packages

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

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