DBMS > Adabas vs. InfluxDB vs. MongoDB vs. Splice Machine vs. Teradata

System Properties Comparison Adabas vs. InfluxDB vs. MongoDB vs. Splice Machine vs. Teradata

Editorial information provided by DB-Engines

Name

Description

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

used typically together with the Natural programming platform

DBMS for storing time series, events and metrics

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Secondary database models

Spatial DBMS

with GEO package

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

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

www.influxdata.com/products/influxdb-overview

www.mongodb.com

splicemachine.com

www.teradata.com

Technical documentation

docs.influxdata.com/influxdb

www.mongodb.com/docs/manual

splicemachine.com/how-it-works

docs.teradata.com

Developer

Software AG

MongoDB, Inc

Splice Machine

Teradata

Initial release

1971

2013

2009

2014

1984

Current release

2.7.6, April 2024

6.0.7, June 2023

3.1, March 2021

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

AGPL 3.0, commercial license available

commercial

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
OS X

through Homebrew

Linux
OS X
Solaris
Windows

hosted
Linux

Data scheme

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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

Secondary indexes

yes

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

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like query language

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

SQL 2016 + extensions

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

HTTP API
JSON over UDP

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

JDBC
Native Spark Datasource
ODBC

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

Supported programming languages

Natural

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

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

Server-side scripts

Stored procedures

in Natural

JavaScript

yes

Java

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

in enterprise version only

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

in enterprise version only

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

ACID

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

In-memory capabilities

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

yes

Depending on used storage engine

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

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

simple rights management via user accounts

Access rights for users and roles

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
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Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
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AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
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ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
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Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
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MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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News

An Introductory Guide to Grafana Alerts
16 May 2024

What to Expect When You’re Expecting InfluxDB: A Guide
14 May 2024

Introduction to Apache Iceberg
9 May 2024

Converting Timestamp to Date in Java
7 May 2024

A Detailed Guide to C# TimeSpan
2 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.