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DBMS > Apache Impala vs. Badger vs. Graph Engine vs. QuestDB

System Properties Comparison Apache Impala vs. Badger vs. Graph Engine vs. QuestDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBadger  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA high performance open source SQL database for time series data
Primary database modelRelational DBMSKey-value storeGraph DBMS
Key-value store
Time Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websiteimpala.apache.orggithub.com/­dgraph-io/­badgerwww.graphengine.ioquestdb.io
Technical documentationimpala.apache.org/­impala-docs.htmlgodoc.org/­github.com/­dgraph-io/­badgerwww.graphengine.io/­docs/­manualquestdb.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDGraph LabsMicrosoftQuestDB Technology Inc
Initial release2013201720102014
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoMIT LicenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Go.NET and CJava (Zero-GC), C++, Rust
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
.NETLinux
macOS
Windows
Data schemeyesschema-freeyesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesnoyesyes
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.nononono
Secondary indexesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSQL with time-series extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesAll languages supporting JDBC/ODBCGoC#
C++
F#
Visual Basic
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioninghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infothrough memory mapped files
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno
More information provided by the system vendor
Apache ImpalaBadgerGraph Engine infoformer name: TrinityQuestDB
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh 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
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More resources
Apache ImpalaBadgerGraph Engine infoformer name: TrinityQuestDB
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