DBMS > Adabas vs. Heroic vs. Hive vs. Hyprcubd vs. XTDB

System Properties Comparison Adabas vs. Heroic vs. Hive vs. Hyprcubd vs. XTDB

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Serverless Time Series DBMS

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

Primary database model

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

github.com/spotify/heroic

hive.apache.org

hyprcubd.com (offline)

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

Technical documentation

spotify.github.io/heroic

cwiki.apache.org/confluence/display/Hive/Home

www.xtdb.com/docs

Developer

Software AG

Spotify

Apache Software Foundation

initially developed by Facebook

Hyprcubd, Inc.

Juxt Ltd.

Initial release

1971

2014

2012

2019

Current release

3.1.3, April 2022

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Clojure

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

All OS with a Java VM

hosted

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

time, int, uint, float, string

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

yes

with add-on product Adabas SQL Gateway

SQL-like DML and DDL statements

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

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

JDBC
ODBC
Thrift

gRPC (https)

HTTP REST
JDBC

Supported programming languages

Natural

C++
Java
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

in Natural

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

selectable replication factor

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

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

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

Access rights for users, groups and roles

token access

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

State agency proves DevOps and mainframes can coexist
12 April 2024, SiliconANGLE News

IBM buys 50-year-old Software AG's enterprise tech units for €2.13B in cash
18 December 2023, The Register

A Second Look at LzLabs' Mainframe Migration
28 June 2017, Virtualization Review

Treehouse Software, Inc. Helps US Foods With Their Mainframe Modernization Initiative
10 April 2023, PerishableNews

Don't rewrite legacy systems for hybrid cloud – integrate them
1 February 2022, ITWeb

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

Apache Software Foundation Announces Apache® Hive 4.0
30 April 2024, GlobeNewswire

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

DataCentral: Uber's Observability and Chargeback Platform
1 February 2024, Uber

provided by Google News

Share this page