DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Fujitsu Enterprise Postgres vs. Heroic vs. LevelDB vs. Teradata

System Properties Comparison Fujitsu Enterprise Postgres vs. Heroic vs. LevelDB vs. Teradata

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonHeroic  Xexclude from comparisonLevelDB  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSTime Series DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.37
Rank#281  Overall
#127  Relational DBMS
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Score2.75
Rank#107  Overall
#19  Key-value stores
Score47.84
Rank#21  Overall
#15  Relational DBMS
Websitewww.postgresql.fastware.comgithub.com/­spotify/­heroicgithub.com/­google/­leveldbwww.teradata.com
Technical documentationwww.postgresql.fastware.com/­product-manualsspotify.github.io/­heroicgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.teradata.com
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologySpotifyGoogleTeradata
Initial release201420111984
Current releaseFujitsu Enterprise Postgres 14, January 20221.23, February 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaC++
Server operating systemsLinux
Windows
Illumos
Linux
OS X
Windows
hosted
Linux
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyes
Secondary indexesyesyes infovia Elasticsearchnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyesnonoyes infoSQL 2016 + extensions
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HQL (Heroic Query Language, a JSON-based language)
HTTP API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functionsnonoyes infoUDFs, stored procedures, table functions in parallel
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashShardingnoneSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard
More information provided by the system vendor
Fujitsu Enterprise PostgresHeroicLevelDBTeradata
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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
Fujitsu Enterprise PostgresHeroicLevelDBTeradata
DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

show all

Recent citations in the news

Fujitsu Develops Column-Oriented Data-Processing Engine Enabling Fast, High-Volume Data Analysis in Database ...
26 February 2015, Fujitsu

Primary Data says stop, Hammerspace, Innodisk cooks some SSDs, and Fujitsu goes blockchain
22 May 2018, The Register

provided by Google News

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

provided by Google News

LevelDB in Ruby — SitePoint
22 October 2014, SitePoint

Microsoft Teams stores auth tokens as cleartext in Windows, Linux, Macs
14 September 2022, BleepingComputer

Pliops unveils XDP-Rocks for RocksDB – Blocks and Files
19 October 2022, Blocks & Files

XanMod, Liquorix Kernels Offer Some Advantages On AMD Ryzen 5 Notebook
26 July 2021, Phoronix

Rust-Based Info Stealers Abuse GitHub Codespaces
19 May 2023, Trend Micro

provided by Google News

Teradata adds support for Apache Iceberg, Delta Lake tables
30 April 2024, InfoWorld

Why We Like The Returns At Teradata (NYSE:TDC)
27 April 2024, Simply Wall St

Unify Analytics Leveraging Amazon Athena and Teradata for Robust Query Federation | Amazon Web Services
23 April 2024, AWS Blog

Teradata Corporation (NYSE:TDC) Q4 2023 Earnings Call Transcript
13 February 2024, Yahoo Finance

An interview with Teradata CFO Claire Bramley
9 February 2024, McKinsey

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Present your product here