DBMS > EJDB vs. Heroic vs. Hypertable vs. StarRocks vs. Teradata Aster

System Properties Comparison EJDB vs. Heroic vs. Hypertable vs. StarRocks vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

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

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

An open source BigTable implementation based on distributed file systems such as Hadoop

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Platform for big data analytics on multistructured data sources and types

Primary database model

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

github.com/Softmotions/ejdb

github.com/spotify/heroic

www.starrocks.io

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

spotify.github.io/heroic

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Softmotions

Spotify

Hypertable Inc.

The Linux Foundation

since Feb 2023

Teradata

Initial release

2012

2014

2009

2020

2005

Current release

0.9.8.11, March 2016

2.5.3, March 2023

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

Open Source

Apache Version 2.0

commercial

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++

C++, Java

Server operating systems

server-less

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

schema-free

yes

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

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

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

APIs and other access methods

in-process shared library

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

C++ API
Thrift

JDBC
MySQL protocol

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

Java

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

R packages

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning (by range and hash)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

selectable replication factor on file system level

yes

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

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

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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