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

DBMS > AllegroGraph vs. Graphite vs. IBM Db2 Event Store vs. Oracle Berkeley DB vs. QuestDB

System Properties Comparison AllegroGraph vs. Graphite vs. IBM Db2 Event Store vs. Oracle Berkeley DB vs. QuestDB

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonGraphite  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperDistributed Event Store optimized for Internet of Things use casesWidely used in-process key-value storeA high performance open source SQL database for time series data
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Time Series DBMSEvent Store
Time Series DBMS
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Time Series DBMS
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score4.83
Rank#67  Overall
#4  Time Series DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Websiteallegrograph.comgithub.com/­graphite-project/­graphite-webwww.ibm.com/­products/­db2-event-storewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlquestdb.io
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlgraphite.readthedocs.iowww.ibm.com/­docs/­en/­db2-event-storedocs.oracle.com/­cd/­E17076_05/­html/­index.htmlquestdb.io/­docs
DeveloperFranz Inc.Chris DavisIBMOracle infooriginally developed by Sleepycat, which was acquired by OracleQuestDB Technology Inc
Initial release20042006201719942014
Current release8.0, December 20232.018.1.40, May 2020
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache 2.0commercial infofree developer edition availableOpen Source infocommercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonC and C++C, Java, C++ (depending on the Berkeley DB edition)Java (Zero-GC), C++, Rust
Server operating systemsLinux
OS X
Windows
Linux
Unix
Linux infoLinux, macOS, Windows for the developer additionAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
macOS
Windows
Data schemeyes infoRDF schemasyesyesschema-freeyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesNumeric data onlyyesnoyes
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.no infobulk load of XML files possiblenonoyes infoonly with the Berkeley DB XML editionno
Secondary indexesyesnonoyesno
SQL infoSupport of SQLSPARQL is used as query languagenoyes infothrough the embedded Spark runtimeyes infoSQL interfaced based on SQLite is availableSQL with time-series extensions
APIs and other access methodsRESTful HTTP API
SPARQL
HTTP API
Sockets
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
JavaScript (Node.js)
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnoyesnono
Triggersyesnonoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodeswith FederationnoneShardingnonehorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneActive-active shard replicationSource-replica replicationSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationnoneEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyes infolockingNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infothrough memory mapped files
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationnofine grained access rights according to SQL-standardno
More information provided by the system vendor
AllegroGraphGraphiteIBM Db2 Event StoreOracle Berkeley DBQuestDB
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
News

How a Neuro-Symbolic AI Approach Can Improve Trust in AI Apps
23 May 2024

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

QuestDB 8.0: Major Release
23 May 2024

QuestDB and Raspberry Pi 5 benchmark, a pocket-sized powerhouse
8 May 2024

Build your own resource monitor with QuestDB and Grafana
6 May 2024

Does "vpmovzxbd" Scare You? Here's Why it Doesn't Have To
12 April 2024

Create an ADS-B flight radar with QuestDB and a Raspberry Pi
8 April 2024

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
AllegroGraphGraphiteIBM Db2 Event StoreOracle Berkeley DBQuestDB
DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Q&A: Can Neuro-Symbolic AI Solve AI’s Weaknesses?
8 April 2024, TDWI

AI predictions for 2024 unveil exciting technological horizons
21 November 2023, Wire19

Neuro-Symbolic AI: The Peak of Artificial Intelligence
16 November 2021, AiThority

The Foundation of Data Fabrics and AI: Semantic Knowledge Graphs - DataScienceCentral.com
19 May 2022, Data Science Central

Franz Releases the First Neuro-Symbolic AI Platform Merging Knowledge Graphs, Generative AI, and Vector Storage
11 December 2023, Datanami

provided by Google News

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

Grafana Labs Announces Mimir Time Series Database
1 April 2022, Datanami

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

The value of time series data and TSDBs
10 June 2021, InfoWorld

provided by Google News

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, ibm.com

IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere
31 May 2018, Data Center Knowledge

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

Best cloud databases of 2022
4 October 2022, ITPro

provided by Google News

Margo Seltzer Named ACM Athena Lecturer for Technical and Mentoring Contributions
26 April 2023, HPCwire

ACM recognizes far-reaching technical achievements with special awards
26 May 2021, EurekAlert

Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag
5 March 2019, ADT Magazine

Oracle buys Sleepycat Software
14 February 2006, MarketWatch

Margo I. Seltzer | Berkman Klein Center
18 August 2020, Berkman Klein Center

provided by Google News

QuestDB snares $12M Series A with hosted version coming soon
3 November 2021, TechCrunch

SQL Extensions for Time-Series Data in QuestDB
11 January 2021, Towards Data Science

QuestDB gets $12M Series A funding amid growing interest in time-series databases
3 November 2021, SiliconANGLE News

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

MindsDB Platform Now Features Over 70 Integrations
4 November 2022, Datanami

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.

Present your product here